This paper aims to develop a novel hierarchical recursive nonsingular terminal sliding mode controller (HRNTSMC), which is designed to stabilize the inverted pendulum (IP). In contrast to existing hierarchical sliding mode controllers (HSMC), the HRNTSMC significantly reduces the chattering problem in control input and improves the convergence speed of errors. In the HRNTSMC design, the IP system is first decoupled into pendulum and cart subsystems. Subsequently, a recursive nonsingular terminal sliding mode controller (RNTSMC) surface is devised for each subsystem to enhance the error convergence rate and attenuate chattering effects. Following this design, the HRNTSMC surface is constructed by the linear combination of the RNTSMC surfaces. Ultimately, the control law of the HRNTSMC is synthesized using the Lyapunov theorem to ensure that the system states converge to zero within a finite time. By invoking disturbances estimation, a linear extended state observer (LESO) is developed for the IP system. To validate the effectiveness, simulation results, including comparison with a conventional hierarchical sliding mode control (CHSMC) and a hierarchical nonsingular terminal sliding mode control (HNTSMC) are presented. These results clearly showcase the excellent performance of this approach, which is characterized by its strong robustness, fast convergence, high tracking accuracy, and reduced chattering in control input. © 2023 by the authors.

This article aims to develop a new Adaptive Proportional Integral Derivative (PID) Nonsingular Dual Terminal Sliding Mode Control, designed for tracking the position of robot manipulators under disturbances and uncertainties. Compared with existing PID Nonsingular Fast Terminal Sliding Mode (PIDNFTSM) controllers, this work effectively avoids singularity problems in control while significantly enhancing the convergence speed of errors. An adaptive reaching law is proposed to estimate the bound information of the first derivative of lumped disturbance by regulating itself based on sliding variables. The overall system stability is proven by using the Lyapunov approach. Subsequent simulation results verify the effectiveness of the proposed controller regarding tracking error reduction, energy efficiency enhancements, and singularity avoidance. © 2023 by the authors.

Background: Structural damage can be caused by various factors such as aging, environmental conditions, and unexpected events like earthquakes. Early detection of damage is crucial to prevent further deterioration, avoid catastrophic failure, and reduce maintenance costs. Damage detection methods that use piezoelectric sensors have gained popularity due to their non-destructive and non-invasive nature. Despite the progress made in the field of damage detection using piezoelectric sensors, there is still a need to improve the accuracy and reliability of those methods. Objective: This study aims to contribute to this by investigating the damage detection hybrid method, which uses the time-of-flight (ToF) criteria of acquired signals besides the energy loss damage index (DI) between damaged and intact states of a specimen, and exploring its possible improvements. The improvement potential in the investigated method regarding the signal processing details and the specification of the ToF used within the method, where the lack of information has been identified. Thus, the present study concentrates on those factors to get more benefit of the suggested method and extend its applicability. Results: The investigated factors play significant role in the accuracy and reliability of the method. By analyzing these criteria, this study contributes to the development of more advanced and reliable damage detection methods that can be applied to a wide range of structures, improving the ability to assess their structural health and safety. This study provides a better understanding of the hybrid method and contributes to the development of more accurate and reliable damage detection methods. The results of this study indicate that the proposed hybrid method effectively detects damage in the structural components under investigation with high accuracy and reliability. Methods: A 2D concrete plate is utilized to apply the proposed methodology. Hereby, various ToF criteria, truncation strategies of the signals, and the number of piezoelectric transducers used in the numerical experiment are examined to investigate their impact on the damage detection accuracy. Conclusion: Performance of the method was found to be significantly affected by selection of the investigated parameters, as well as of the number and placement of sensors. The findings suggest that a thorough analysis of these criteria can lead to further improvements in the accuracy and reliability of damage detection methods. © 2023, The Author(s).

Early damage identification and continuous system monitoring save dramatically maintenance costs and increase the lifespan of priceless structures. Convolutional neural networks (CNNs) have attracted the attention of the structural health monitoring (SHM) community in recent years due to their great potential for identifying underlying data patterns. However, employing two-dimensional convolutional layers in a CNN necessitates the use of strong computing resources. Therefore, based on the present state-of-the-art technical solutions, a two-dimensional CNN is not suitable for real-time SHM applications with stand-alone processing units. One-dimensional convolutional networks (1D-CNN) have recently been employed in Ultrasonic Guided Wave-based (UGW-based) damage detection to address the aforementioned disadvantage. In this paper, a methodology for damage assessment at three levels – detection, localization, and characterization – based on 1D-CNN is put forward. Furthermore, the sequence length of the time-domain signals is significantly shortened by the application of a novel approach for processing them. Additionally, it is shown to what extend this method can improve the distinguishability between datapoints obtained from various damage scenarios. Consequently, by reducing the dimensionality of the problem, the proposed approach significantly reduces the memory usage of the classification algorithm. Experimental measurements as well as Numerical simulations, in which various damage scenarios such as corrosion, circular hole and cracks have been considered, are carried out to evaluate the efficacy of the proposed algorithm. It is shown that the suggested approach has benefits in terms of true classification rate of instances (above 93 percent for detection, localization, and characterization), computing time, in-situ monitoring, and noise resilience. © 2022 Elsevier Ltd

Identification of damage in its early stage can have a great contribution in decreasing the maintenance costs and pro-longing the life of valuable structures. Although conventional damage detection techniques have a mature background, their widespread application in industrial practice is still missing. In recent years the application of Machine Learning (ML) algorithms have been more and more exploited in structural health monitoring systems (SHM). Because of the superior capabilities of ML approaches in recognizing and classifying available patterns in a dataset, they have demonstrated a significant improvement in traditional damage identification algorithms. This review study focuses on the use of machine learning (ML) approaches in Ultrasonic Guided Wave (UGW)-based SHM, in which a structure is continually monitored using permanent sensors. Accordingly, multiple steps required for performing damage detection through UGWs are stated. Moreover, it is outlined that the employment of ML techniques for UGW-based damage detection can be sub-tended into two main phases: (1) extracting features from the data set, and reducing the dimension of the data space, (2) processing the patterns for revealing patterns, and classification of instances. With this regard, the most frequent techniques for the realization of those two phases are elaborated. This study shows the great potential of ML algorithms to as-sist and enhance UGW-based damage detection algorithms. © 2022, Prognostics and Health Management Society. All rights reserved.

Drilling into unknown soil during mechanized tunneling may cause damage of the tunnel boring machine or delays in the construction process. A full waveform inversion can prevent these issues supplying a detailed image of the subsoil, but claims several challenges like the need for an adequate method or the need for an appropriate utilization of seismic sources and receivers. In this research, a small-scale surrogate model is constructed in order to create representative tunneling field data in a laser laboratory. With the experimental model, ultrasonic data is generated. After constructing an adequate forward model, two non-gradient full waveform inversion methods based on parameter identification are applied to the measurement data in order to determine the inner structure of the model out of seismic waveforms. Furthermore, the positioning of seismic sources and receivers is investigated. The algorithms are found to perform well on the acquired measurement data, with different precisions dependent on the utilized method and on the source-receiver configuration. The comparability of the ultrasonic data to tunneling field data is analyzed. © 2021 Elsevier Ltd

Due to their efficiency in standard control problems, proportional-integral-derivative (PID) controllers are widely used in industrial control systems. Although this controller has been established as a control standard, tuning of its parameters and finding their optimal combination still represents a challenge, particularly under changing operating conditions, where control designer cannot rely on the invariance of the plant model. Tuning of the proportional, integral and derivative gain of a PID controller represents an optimization task, for which we propose in this work a solution based on artificial intelligence (AI) approach using radial basis (RB) function for activation of neural networks (NN) which adapt the controller gains and learn the plant model in order to account for the controller influence on the control outcome. The controller is implemented in a discrete-time system which enables real-time learning and implementation. The effectiveness of the proposed controller is tested on a benchmark example of a discrete-time model of a cantilever beam, obtained through the subspace model identification. © 2021 IEEE.

Vulnerability of structures to damage during their service time brings up the necessity of design and implementation of an intelligent procedure to assure the health of the structure. In the sight of this requisite, current work deals with extending the capability of a dual Kalman filter (DKF) state estimation scheme to assist vibration-based health monitoring methods. This is met by estimating the response of the structure for locations at which a sensor cannot be placed. The capability of the DKF method in the estimation of states of a linear system with an unknown input has been presented in various recent works. In this paper, a DKF approach incorporated with a reduced order structural model (in this case an aluminum plate) is utilized to obtain an estimation of applied force and the response of the structure in terms of acceleration, velocity, and displacement. These estimations are based on measured accelerations at a limited number of points on the aluminum plate as well as the state-space model of the dynamic system. Numerical simulations and experimental works are performed to obtain the mentioned datasets. To assess the robustness of the method concerning various conditions, the effect of the frequency, as well as type of the function of the input force on the validity of the method, is presented. Moreover, it is shown to what extent the number of selected modes in model reduction procedure can influence the accuracy of the DKF technique. © 2021, Springer Nature Switzerland AG.

A novel approach to active structural health monitoring and damage detection of massive reinforced concrete structures using piezoelectric smart aggregates is presented in this paper. An innovative three-dimensional damage index, based on wavelet signal decomposition and energy of wave propagation, is derived in matrix form. Although the proposed three-dimensional damage index can be used for all types of reinforced concrete structures, it is primarily recommended for massive infrastructure buildings. The approach proposed in this paper is theoretically considered for an arbitrary shape of a reinforced concrete element, and it is numerically verified for various scenarios by varying the geometry of reinforced concrete elements, as well as the position, size and quantity of damage. Quasi-static analysis of piezoelectric smart aggregates is modelled using a standard finite element method, and the explicit finite element method is successfully applied in this research for modelling propagation of ultrasonic waves. The results based on numerically generated simulations indicate that the new approach to non-destructive damage detection using three-dimensional damage indexes is quite promising. © 2021 Union of Croatian Civil Engineers and Technicians. All rights reserved.

Optimizing the reliability and the robustness of a design is important but often unaffordable due to high sample requirements. Surrogate models based on statistical and machine learning methods are used to increase the sample efficiency. However, for higher dimensional or multi-modal systems, surrogate models may also require a large amount of samples to achieve good results. We propose a sequential sampling strategy for the surrogate based solution of multi-objective reliability based robust design optimization problems. Proposed local Latin hypercube refinement (LoLHR) strategy is model-agnostic and can be combined with any surrogate model because there is no free lunch but possibly a budget one. The proposed method is compared to stationary sampling as well as other proposed strategies from the literature. Gaussian process and support vector regression are both used as surrogate models. Empirical evidence is presented, showing that LoLHR achieves on average better results compared to other surrogate based strategies on the tested examples. © 2021 Elsevier B.V.

A proportional-integral-derivative (PID) controller is one of the most popular and commonly used controllers. Although this controller has been established as a control standard, still it has to cope with some difficulties. Tuning the parameters (proportional, integral and derivative gains) of a PID controller manually requires a large experience and can be a tedious task. In this work, we propose an optimization based approach to automatically tune these three parameters as the system is driven towards its desired behaviour. The parameters of the PID controller are tuned using a neural network (NN) with a radial basis (RB) activation function, while the parameters of the NN are optimized using a stochastic gradient descent (SGD) algorithm. This enables the system to learn online in realtime. Further, this method is tested in Simulink environment on a benchmark of the vibration suppression for a clamped-free flexible aluminum beam. The starting point for the controller design is the model of the beam obtained through the subspace model identification. Further on, using the NN the model update is performed along with the PID parameter optimization. © 2021 IEEE.

Performance of smart piezoelectric structures strongly depends on placement of integrated piezoelectric actuators and sensors, which may be implemented in the form of thin film layers on the structure surface or embedded within the structure. In both cases actuator and sensor placement plays an important role, since after applying they remain permanently integrated with structure. In this paper the optimization procedure for piezoelectric structures with curved surfaces is proposed based on the Software-in-the-Loop (SiL) methodology and balanced modal order reduction in combination with H2 and H∞ norms used in placement indices. The optimization procedure is a global one, since it seeks for optima across the entire domain of the structure. A special challenge is tackling the problem of curved surfaces. This problem is solved in this work for a funnel shaped structure – inlet of the magnetic resonance imaging tomopraph. A thorough mesh convergence study with respect to the eigenfrequency analysis is performed in order to obtain a reliable numeric finite element model for further optimization purposes. Material parameter optimization is performed as well. Based on placement indices optimal placement study is performed under consideration of several eigenmodes of interest. The optimization is performed for individual modes as well as for simultaneous consideration of multiple modes. The SiL approach with recurrent communication in each iteration of the optimization between the numerical simulation FE software and optimization tool designed in Python is implemented through the evaluation of the placement indices for candidate locations over the entire curved surface of the structure. Depending on support conditions, optimal locations of piezoelectric actuators and sensors are proposed. © 2020 Elsevier Ltd

The presence of actuators and sensors characterizes inevitably all operating processes in engineering, industry or applied research. Careful selection of the actuator/sensor placement can substantially improve performance of systems and contribute in turn to considerable savings. With respect to suppression of unwanted vibrations in lightweight structures by applying appropriate control, piezoelectric films represent convenient solution since they can be easily integrated with structures and due to their lightweight character they do not influence the overall mass of structures, but may contribute to changing stiffness in accordance with applied control and in that way actively perform adapting the structure's properties to changing environmental conditions. In this paper a global optimization procedure for placement of piezoelectric actuators and sensors on lightweight structures prone to vibration is presented. Optimization is model-based and assumes software-in-the-loop coupling of finite element numeric software with corresponding programming solutions to provide iterative exploration of a predefined set of candidate locations with respect to defined objective functions. The objective here is defined in terms of H2 and H∞ norms constructed upon the eigenforms of structures, which provides maximization of the control influence or maximal sensing effect. Implementation is illustrated by two examples of structures with curved surfaces - cylindrical and funnel shaped structure. © 2020 IEEE.

A full waveform inversion may be utilized as a promising tool to invert the properties of a spatial model out of seismic waveforms, but in turn may claim a high computational effort if the inversion method is not effective. Unscented hybrid simulated annealing, which is developed for an application in mechanized tunneling, is an optimization method that combines the metaheuristic simulated annealing with the unscented Kalman filter. The method needs a priori knowledge in the form of a user-defined parametrization, but therefore may invert the structure effectively and precisely. In this work, the authors apply the novel method on laboratory-generated seismic data. In a first step, three concrete plates with different structural anomalies are constructed. Seismic data is acquired and implemented into the optimization algorithm to invert the positions, shapes, and the material parameters of the structural anomalies. The authors find that the algorithm performs well on the generated data, reconstructing the structural anomalies with a satisfying precision during a low number of forward simulations. © 2020 Elsevier B.V.

The lack of anomaly detection methods during mechanized tunnelling can cause financial loss and deficits in drilling time. On-site excavation requires hard obstacles to be recognized prior to drilling in order to avoid damaging the tunnel boring machine and to adjust the propagation velocity. The efficiency of the structural anomaly detection can be increased with intelligent optimization techniques and machine learning. In this research, the anomaly in a simple structure is detected by comparing the experimental measurements of the structural vibrations with numerical simulations using parameter estimation methods. © 2019 Elsevier Ltd

In this paper, the hybrid algorithm for localization of damage and defects is implemented on the concrete plate-like structures for localizing the clay and gypsum inclusions. The hybrid approach employs fast discrete wavelet decomposition of sensor output signals, as well as energy and time of flight criteria. The applied localization algorithm is verified both experimentally and numerically on the concrete plates with one and two inclusions. The experiment is conducted in controlled laboratory conditions, using a piezoelectric actuator for excitation of the wave propagation in the structure, while the ultrasonic laser is used for measuring vibrations at the sensor locations. Numerical simulation of wave propagation is done using the explicit finite element method on 3D models. The numerically obtained results are in full correspondence with the experimental results. The images of material defects positions obtained by the hybrid approach show a good agreement with the actual positions, which indicates a good potential of the used approach in localization of various types of material defects in plate-like concrete structures. © 2019 Elsevier Ltd

In the controllers that are synthesized on a nominal model of a nonlinear plant, the parametric matched uncertainties and nonlinear/unmodelled dynamics of the high order nature can significantly affect the performance of the closedloop system. On this note, owing to the robust characteristic of the sliding mode observer against modelling perturbations, measurement noise, and unknown disturbances and due to the non-fragile behaviour of the Kalman filter against process noise, a mixed Kalman sliding mode state-observer is proposed and later enhanced by the addition of an intelligent fuzzy agent. In light of the proposed technique, the chattering phenomena and the conservative boundary neighboring layer of the high gain sliding mode observer are addressed. Then, a robust active disturbance rejection controller is developed by using the static feedback of the estimated states using a direct Lyapunov quadratic stability theorem. The reduced order plant for control design purposes is subjected to some simulated square-integrable disturbances and is assumed to have mismatched uncertainties in the system matrices. Finally, the robust performance of the closed-loop scheme with respect to the mentioned perturbation signals and modelling imperfections is tested by implementing the control system on a mechanical vibrating smart cantilever beam. © 2019 International Institute of Acoustics and Vibrations. All rights reserved.

In this paper, the windup problem in active vibration control (AVC) is studied systematically. Instead of evaluating the performance of several anti-windup compensators implemented on independent abstract simulation problems, a unified benchmark setup in active-damping control (ADC) is used. The investigated anti-windup schemes (analysis and synthesis) are adapted to the disturbance rejection control. Large attention is given to capture the similarities and differences of the methods in dealing with the windup event in a practical context. Therefore, instead of categorizing the methods into static and non-static methods or model recovery and direct linear anti-windup schemes, a logical route is followed to highlight the significance of each method. The mathematical interpretations of the methods are provided for the vibration engineer while delivering forthright implementation algorithms for AVC. The tackled methods are unified on a state space model obtained from the frequency-domain subspace system identification approach. Practical issues that may raise for each technique are mentioned, and detained guidelines are provided for tuning each algorithm. Finally, in order to compare the compensated system's performance, comprehensive time-domain studies are carried out by separating the transient response of the compensated systems to three modes: linear mode, where the actuation nonlinearity is inactive; the nonlinear mode, where the windup event is in progress, and finally, the output mismatch rejection mode, where the windup incident is over, but performance degradation is still present. © 2018 Elsevier Ltd

This paper presents an experimental–numerical analysis of damage localization of concrete plate-like elements on the basis of hybrid approach. The proposed hybrid approach uses the fast discrete wavelet transform, energy approach, and time of flight criterion for the purpose of localization of single and multidamage problems inside or on the periphery of concrete elements. Verification of the proposed damage localization approach has been performed under laboratory conditions using a laser scanning-based system with piezoelectric excitation of the wave propagation. Numerical simulation of the wave propagation is performed using the explicit finite element method using 3D models with linear-elastic material model of concrete with Rayleigh damping. The Rayleigh damping coefficients are determined on the basis of experimental data and implemented in numerical models. Validation of the numerical model is conducted, based on the comparison with sensor output signals obtained through experimental measuring and a very good agreement of results is obtained. The proposed hybrid approach to damage localization is verified using 15 different models/specimens, varying the number, shape (circular or notched), and position of damage, as well as the number and placement of actuators/sensors. For all the analyzed scenarios, the hybrid approach successfully localized the damage even for the least number of used sensor positions. In the models with the circular damage, the damage image created on the basis of the hybrid approach is almost identical to the actual shape of the damage, indicating a good potential of the method for damage localization. © 2018 John Wiley & Sons, Ltd.

In this paper, we introduce a new framework for running the finite element (FE) packages inside an online Loop together with MATLAB. Contrary to the Hardware-in-the-Loop techniques (HiL), in the proposed Software-in-the-Loop framework (SiL), the FE package represents a simulation platform replicating the real system which can be out of access due to several strategic reasons, e.g., costs and accessibility. Practically, SiL for sophisticated structural design and multi-physical simulations provides a platform for preliminary tests before prototyping and mass production. This feature may reduce the new product's costs significantly and may add several flexibilities in implementing different instruments with the goal of shortlisting the most cost-effective ones before moving to real-time experiments for the civil and mechanical systems. The proposed SiL interconnection is not limited to ABAQUS as long as the host FE package is capable of executing user-defined commands in FORTRAN language. The focal point of this research is on using the compiled FORTRAN subroutine as a messenger between ABAQUS/CAE kernel and MATLAB Engine. In order to show the generality of the proposed scheme, the limitations of the available SiL schemes in the literature are addressed in this paper. Additionally, all technical details for establishing the connection between FEM and MATLAB are provided for the interested reader. Finally, two numerical sub-problems are defined for offline and online post-processing, i.e., offline optimization and closed-loop system performance analysis in control theory. © 2018 Techno-Press, Ltd.

Black-box system identification is subjected to the modelling uncertainties that are propagated from the non-parametric model of the system in time/frequency-domain. Unlike classical H1/H2 spectral analysis, in the recent robust Local Polynomial Method (LPM), the modelling variances are separated to noise contribution and nonlinear contribution while suppressing the transient noise. On the other hand, without an appropriate weighting on the objective function in the system identification methods, the acquired model is subjected to bias. Consequently, in this paper the weighted regression problem in subspace frequency-domain system identification is revisited in order to have an unbiased estimate of the frequency response matrix of a flexible manipulator as a multi-input multi-output lightly-damped system. Although the unbiased parametric model representing the best linear approximation (BLA) of the system in this combination is a reliable framework for the control design, it is limited for a specific signal-to-noise (SNR) ratio and standard deviation (STD) of the involved input excitations. As a result, in this paper, an additional step is carried out to investigate the sensitivity of the identified model w.r.t. SNR/STD in order to provide an uncertainty interval for robust control design. © 2018

In this paper, a model-based output feedback recurrent wavelet neural network (RWNN) controller is proposed for a class of nonlinear MIMO systems with time-varying matched/mismatched uncertainties. The proposed RWNN emulator adaptively trains to follow an ideal state-feedback controller which is designed on the underlying linear model (ULM) of the plant. Simultaneously, the control system employs an adaptive neural network (NN) mechanism to estimate the mismatch between the RWNN controller and this ideal control law. As a result, the conservatism associated with the classical robust control methods where the controller is synthesized based on worst-case bounds is addressed. Moreover, in order to generalize the subjected class of the investigatable plants, the echo-state feature of adaptive RWNN is used to contribute to the performance of nonminimum phase systems. Accordingly, in the context of flexible smart structures with non-collocated sensor/actuator configuration, a delayed feedback is added in the network which brings about a better match between the model output and the measured output. As a result, even for systems with an unknown Lipschitz constant of lumped uncertainty, the controller can be trained online to compensate with an additional revision of the control law following some Lyapunov-based adaptive stabilizing rules. Additionally, the current approach is proposed as an alternative to the hot topic of nonlinear system identification-based control synthesis where the exact structure of the nonlinearity is required. © 2017 Elsevier Ltd

In this paper, an observer-based feedback/feedforward model predictive control (MPC) algorithm is developed for addressing the active vibration control (AVC) of lightly damped structures. For this purpose, the feedback control design process is formulated in the framework of disturbance rejection control (DRC) and a repetitive MPC is adapted to guarantee the robust asymptotic stability of the closed-loop system. To this end, a recursive least squares (RLS) algorithm is engaged for online estimation of the disturbance signal, and the estimated disturbance is feed-forwarded through the control channels. The mismatched disturbance is considered as a broadband energy bounded unknown signal independent of the control input, and the internal model principle is adjusted to account for its governing dynamics. For the sake of relieving the computational burden of online optimization in MPC scheme, within the broad prediction horizons, a set of orthonormal Laguerre functions is utilized. The controller design is carried out on a reduced-order model of the experimental system in the nominal frequency range of operation. Accordingly, the system model is constructed following the frequency-domain subspace system identification method. Comprehensive experimental analyses in both time-/frequency-domain are performed to investigate the robustness of the AVC system regarding the unmodeled dynamics, parametric uncertainties, and external noises. Additionally, the spillover effect of the actuation authorities and saturation of the active elements as two common issues of AVC systems are addressed. Copyright © 2018 John Wiley & Sons, Ltd.

In this paper, the impact of various input excitation scenarios on two different MIMO linear non-parametric modeling schemes is investigated in the frequency-domain. It is intended to provide insight into the optimal experiment design that not only provides the best linear approximation (BLA) of the frequency response functions (FRFs), but also delivers the means for assessing the variance of the estimations. Finding the mathematical representations of the variances in terms of the estimation coherence and noise/nonlinearity contributions are of critical importance for the frequency-domain system identification where the objective function needs to be weighted in the parametrization step. The input excitation signal design is tackled in two cases, i.e., multiple single-reference experiments based on the zero-mean Gaussian and the colored noise signal, the random-phase multisine, the Schroeder multisine, and minimized crest factor multisine; and multi-reference experiments based on the Hadamard matrix, and the so-called orthogonal multisine approach, which additionally examines the coupling between the input channels. The time-domain data from both cases are taken into the classical H1 spectral analysis as well as the robust local polynomial method (LPM) to extract the BLAs. The results are applied for data-driven modeling of a flexible beam as a model of a flexible robotic arm. © 2018

This work presents a flexible and effective methodology for locating and characterizing the disturbance zones ahead of the underground tunnel face by elastic full-waveform inversion (FWI) enhanced with the parametric level-set representation. By using the unscented Kalman filter as the inversion machinary, the inversion process is completely free from gradient calculations and able to provide uncertainty bounds of the estimated model. The conceptual methodology is verified through successful reconstructions of single- and multiple-disturbance objects in a simple 2D frequency domain model. In the synthetic tunnel reconnaissance tests, the special characteristics of the tunnel seismic waves in the time domain are described, and the results of SPECFEM2D simulation and a qualitative evaluation of the simulated tunnel seismic waveforms are shown. The computer model and its simulated tunnel seismic waveform data are eventually used to reconstruct the geological scenarios, whose disturbance is present in the form of a single object and multiple discontinuous objects, in a parsimonious and flexible manner. Although further validations using laboratory or in-situ measurements and the use of fully 3D model are needed to prove the practicality of this approach, the current results are encouraging and promising to apply FWI in tunneling practice as an advanced tool for looking ahead of the tunnel face. © 2018 Elsevier Ltd

This paper presents a disturbance rejection-based solution to the problem of robust output regulation. The mismatch between the underlying plant and its nominal mathematical model is formulated by two disturbance classes. The first class is assumed to be generated by an autonomous linear system while for the second class no specific dynamical structure is considered. Accordingly, the robustness of the closed-loop system against the first disturbance class is achieved by following the internal model principle. On the other hand, in the framework of disturbance rejection control, an extended state observer (ESO) is designed to approximate and compensate for the second class, i.e., unstructured disturbances. As a result, the proposed output regulation method can deal with a vast range of uncertainties. Finally, the stability of the closed-loop system based on the proposed compound controller is carried out via Lyapunov and center manifold analyses, and some results on the robust output regulation are drawn. A representative simulation example is also presented to show the effectiveness of the control method. © 2018 Mehran Hosseini-Pishrobat et al.

A robust nonfragile observer-based controller for a linear time-invariant system with structured uncertainty is introduced. The H∞ robust stability of the closed-loop system is guaranteed by use of the Lyapunov theorem in the presence of undesirable disturbance. For the sake of addressing the fragility problem, independent sets of time-dependent gain-uncertainties are assumed to be existing for the controller and the observer elements. In order to satisfy the arbitrary H2-normed constraints for the control system and to enable automatic determination of the optimal H∞ bound of the performance functions in disturbance rejection control, additional necessary and sufficient conditions are presented in a linear matrix equality/inequality framework. The H∞ observer-based controller is then transformed into an optimization problem of coupled set of linear matrix equalities/inequality that can be solved iteratively by use of numerical software such as Scilab. Finally, concerning the evaluation of the performance of the controller, the control system is implemented in real time on a mechanical system, aiming at vibration suppression. The plant under study is a multi-input single-output clamped-free piezo-laminated smart beam. The nominal mathematical reduced-order model of the beam with piezo-actuators is used to design the proposed controller and then the control system is implemented experimentally on the full-order real-time system. The results show that the closed-loop system has a robust performance in rejecting the disturbance in the presence of the structured uncertainty and in the presence of the unmodeled dynamics. © 2016, © The Author(s) 2016.

This paper reports an immersion and invariance (I&I)–based robust nonlinear controller for atomic force microscope (AFM) applications. The AFM dynamics is prone to chaos, which, in practice, leads to performance degradation and inaccurate measurements. Therefore, we design a nonlinear tracking controller that stabilizes the AFM dynamics around a desired periodic orbit. To this end, in the tracking error state space, we define a target invariant manifold, on which the system dynamics fulfills the control objective. First, considering a nominal case with full state measurement and no modeling uncertainty, we design an I&I controller to render the target manifold exponentially attractive. Next, we consider an uncertain AFM dynamics, in which only the displacement of the probe cantilever is measured. In the framework of the I&I method, we recast the robust output feedback control problem as the immersion of the output feedback closed-loop system into the nominal full state one. For this purpose, we define another target invariant manifold that recovers the performance of the nominal control system. Moreover, to handle large uncertainty/disturbances, we incorporate the method of active disturbance rejection into the I&I output feedback control. Through Lyapunov-based analysis of the closed-loop stability and robustness, we show the semiglobal practical stability and convergence of the tracking error dynamics. Finally, we present a set of detailed, comparative software simulations to assess the effectiveness of the control method. © 2018 John Wiley & Sons, Ltd.

In this note, disturbance rejection control (DRC) based on unknown input observation (UIO), and disturbance-observer based control (DOBC) methods are revisited for a class of MIMO systems with mismatch disturbance conditions. In both of these methods, the estimated disturbance is considered to be in the feedback channel. The disturbance term could represent either unknown mismatched signals penetrating the states, or unknown dynamics not captured in the modeling process, or physical parameter variations not accounted for in the mathematical model of the plant. Unlike the high-gain approaches and variable structure methods, a systematic synthesis of the state/disturbance observer-based controller is carried out. For this purpose, first, using a series of singular value decompositions, the linearized plant is transformed into disturbance-free and disturbance-dependent subsystems. Then, functional state reconstruction based on generalized detectability concept is proposed for the disturbance-free part. Then, a DRC based on quadratic stability theorem is employed to guarantee the performance of the closed-loop system. An important contribution offered in this article is the independence of the estimated disturbance from the control input which seems to be missing in the literature for disturbance decoupling problems. In the second method, DOBC is reconsidered with the aim of achieving a high level of robustness against modeling uncertainties and matched/mismatched disturbances, while at the same time retaining performance. Accordingly, unlike the first method, DRC, full information state observation is developed independent of the disturbance estimation. An advantage of such a combination is that disturbance estimation does not involve output derivatives. Finally, the case of systems with matched disturbances is presented as a corollary of the main results. © 2017 The Franklin Institute

In the paper, a novel approach for damage localization in reinforced concrete plates, based on the computational analysis of piezoelectric smart aggregates, has been presented. The hybrid approach for damage localization is based on two criteria: wave propagation energy and time of flight. The comprehensive numerical analysis using standard and explicit finite element method has been conducted. In addition, the proposed algorithm of the hybrid method has been coded in MATLAB. The approach has been verified numerically using different square reinforced concrete plate models, considering different number, position and size of damage, as well as different number and position of the piezoelectric smart aggregates. Obtained results confirm the successful application of the novel approach to the damage localization. © 2017 Elsevier Ltd

This paper presents the dynamic modeling of a piezolaminated plate considering geometrical nonlinearities. The piezo-actuator and piezo-sensor are connected via proportional derivative feedback control law. The Hamilton’s principle is used to extract the strong form of the equation of motion with the reflection of the higher order strain terms by means of the strain–displacement relationship of the von Karman type. Then the nonlinear partial differential equation (PDE) obtained is converted to a nonlinear algebraic equation by employing the combination of harmonic balance method and single-mode Galerkin’s technique. Finally, the vibration suppression performance and sensitivity of the dynamic response is evaluated for various control parameters and magnitudes of external disturbance. © 2017 World Scientific Publishing Company

In this paper, the dynamic modelling and active vibration control of a piezolaminated plate with geometrical nonlinearities are investigated using a semi-analytical approach. For active vibration control purposes, the core orthotropic elastic layer is assumed to be perfectly bonded with two piezo-layers on its top and bottom surfaces which act as sensor and actuator, respectively. In the modelling procedure, the piezo-layers are assumed to be connected via a proportional derivative (PD) feedback control law. Hamilton's principle is employed to acquire the strong form of the dynamic equation in terms of additional higher order strain expressions by means of von Karman strain-displacement correlation. The obtained nonlinear partial differential equation (NPDE) is converted to a system of nonlinear ordinary differential equations (NODEs) by engaging Galerkin method and using the orthogonality of shape functions for the simply supported boundary conditions. Then, the resulting system of NODEs is solved numerically by employing the built-in Mathematica function, “NDSolve”. Next, the vibration attenuation performance is evaluated and sensitivity of the closed-loop system is investigated for several control parameters and the external disturbance parameters. The proposed solution in open loop configuration is validated by finite element (FE) package ABAQUS both in the spatial domain and for the time-/frequency-dependent response. © 2016 Elsevier B.V.

The implementation of active monitoring systems to diagnose damage to reinforced concrete structures using piezoelectric smart aggregates, and based on wave propagation, ranks among the world's most advanced research activities. Original models, with parametric analysis of the damage index variation problem, depending on the size, position and orientation of cracks, are presented in the paper. Numerical modelling of wave propagation in reinforced concrete is conducted using the explicit finite element method, which is highly effective for this purpose.

This paper proposes a method for finite element (FE) model updating of civil structures. The method is a hybrid global optimization algorithm combining simulated annealing (SA) with the unscented Kalman filter (UKF). The objective function in the optimization problem can be defined in the modal, time, or frequency domains. The algorithm improves the accuracy, convergence rate, and computational cost of the SA algorithm by local improvements of the accepted candidates though the UKF. The proposed methodology is validated using a mathematical function and numerically simulated response data from linear and nonlinear FE models of realistic three-dimensional structures. © 2016 Elsevier Ltd

In this research, we have proposed a methodology for experimental identification of modal parameters based on measurement of the frequency responses of structures with complex geometries and performed an overall investigation of structural behavior on a funnel-shaped inlet of magnetic resonance tomograph. Several identification methods are implemented and compared: complex exponential, least-squares complex exponential, and polyreference least-squares complex exponential. We have implemented the modal parameter identification methodology within our own graphical user interface supported by MATLAB to create an independent tool for modal analysis. The estimation methods are compared and the comparison results are summarized showing based on tabular representation and stabilization diagrams significant advantage of the proposed methodology for determining eigenfrequencies, damping coefficients, mode shapes, and residues for complex structures investigated in broad band of frequencies. Runtime for the execution of algorithms vary depending on the applied method, assumed order of the model used for estimation, and the number of measurements, that is, inputs and outputs. © SAGE Publications Ltd.

This work shows that nonlinear Kalman filters can be applied very effectively for the calibration of geomaterial parameters for geomechanical modeling in mechanized tunneling, using tunneling-induced settlements and horizontal displacements. The data curves measured along tunnel excavation steps, which exhibit a nonlinear relationship with respect to soil parameters and are prone to measurement inaccuracies, are utilized in combination with finite element modeling to estimate the underlying soil parameters, using a sequential inference framework: the nonlinear Kalman filtering. The paper shows the comparative performance of the two types of nonlinear Kalman filters that are effective for the identification of soil parameters in terms of convergence speed and accuracy: the extended Kalman filter (EKF) and the sigma-point Kalman filter (SPKF). The effectiveness of the two Kalman filters for inverse analysis is demonstrated through computer simulations for identifying a number of important constitutive parameters of the hardening soil model in the context of mechanized tunneling. © 2015 American Society of Civil Engineers.

In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system. © 2016 Elsevier Ltd. All rights reserved.

A new hybridized global optimization method that combines simulated annealing global search with unscented Kalman filter minimization is proposed to solve waveform inversion for predicting ahead of the underground tunnel face. The authors demonstrate in this work fast and reliable convergence of this new algorithm through validation of optimization of a multi-minima test function and inversion of synthetic tunnel seismic waveforms to predict the geological structure ahead of the tunnel face. With regard to the engineering application, the successful identification of the true model by minimizing a multimodal misfit functional for wide feasible bounds of the model parameters confirms that waveform inversion by the improved global optimization method is promising for practical applications with real measurement data. © 2015 Elsevier B.V.

Research and development of active monitoring systems for reinforced concrete structures should lead to improved structural safety and reliability. Numerical models of active monitoring and damage detection systems can help in the development and implementation of these systems. Modeling of damage detection process in a concrete beam with piezoelectric sensors/actuators based on wave propagation is investigated in this paper. Numerical modeling process is divided into two parts: (1) piezoelectric smart aggregates (SA), and (2) wave propagation models. Displacement obtained in the SA model is used as an input parameter for the modeling of wave propagation. Wavelet analysis is used as a signal processing tool and the damage index is calculated based on the wave energy. In this paper root-mean-square deviation (RMSD) damage index is used. Damage indices obtained by this numerical analysis are compared with experimental results. Very good fit between the finite element (FE) results and experimental results confirm a good FE approach of this problem. © 2015 Elsevier Ltd. All rights reserved.

In this paper a method of finding optimal positions for piezoelectric actuators and sensors on different structures is presented. The genetic algorithm and multi-objective genetic algorithm are selected for optimization and H<inf>∞</inf> norm is defined as a cost function for the optimization process. To optimize the placement concerning the selected modes simultaneously, the multi-objective genetic algorithm is used. The optimization is investigated for two different structures: a cantilever beam and a simply supported plate. Vibrating structures are controlled in a closed loop with feedback gains, which are obtained using optimal LQ control strategy. Finally, output of a structure with optimized placement is compared with the output of the structure with an arbitrary, non-optimal placement of piezoelectric patches. Copyright © 2015 Techno-Press, Ltd.

Direct measurement of relevant system parameters often represents a problem due to different limitations. In geomechanics, measurement of geotechnical material constants which constitute a material model is usually a very diffcult task even with modern test equipment. Back-analysis has proved to be a more effcient and more economic method for identifying material constants because it needs measurement data such as settlements, pore pressures, etc., which are directly measurable, as inputs. Among many model parameter identification methods, the Kalman filter method has been applied very effectively in recent years. In this paper, the extended Kalman filter-local iteration procedure incorporated with finite element analysis (FEA) software has been implemented. In order to prove the effciency of the method, parameter identification has been performed for a nonlinear geotechnical model. © 2014 published by EDP Sciences.

This paper presents the user defined nine-node piezoelectric shell element and its implementation within a user element subroutine for modeling and analysis of thin-walled active composite structures. The element has been implemented within commercial finite element software ABAQUS. Application of the element covers modeling of arbitrary thin-walled structures also with complex geometries, whereby the automated mesh generation has been accomplished by developing a Python based interface for meshing procedure. In order to be able to perform the post-processing, a special adaptation of the user element had to be performed for visualization purposes. The implemented element regards the piezoelectric thin layers polarized in the thickness direction and it is based on the e31 piezoelectric effect. It has been also shown that this biquadratic nine-node element based on degenerated shell approach is less prone to locking effects and more suitable for implementation with curved structures. Through several examples the accuracy of the implemented user defined shell element as well as of the Python-based mesh extension has been demonstrated, along with the possibilities for post-processing. Meshing the structures with the nine-node user element is not third party software dependent. © 2014 The Author(s).

In this paper, the class of linear discrete-time descriptor systems with time-varying exogenous disturbance are considered. Three sufficient conditions for the finite time boundedness and finite-time stability of linear discrete-time descriptor systems are presented. The stability conditions are reduced to a feasibility problem involving linear matrix inequalities. A numerical example has been provided to show the advantage of derived results. © 2013 IEEE.

In this paper, we consider the problem of finite-time stability for a class of linear singular time-delay systems. New delay dependent stability conditions have been derived using the approach based on the Lyapunov-like functions and their properties on the subspace of consistent initial conditions. The stability conditions are presented in the form of linear matrix inequalities. A numerical example has been provided to show the advantage of derived results. © 2013 IEEE.

Simulation of mechanized tunneling and on-site excavation require very good knowledge of the geomechanical and material properties. Identification of the material must be fast and continuously performed during tunnel excavation for the best possible strategies for advancing the tunnel boring machine. We present in this work the use of the extended Kalman filter (EKF) for identification of the inclined fault zone ahead of the face. The EKF showed fast and stable convergence of the model parameters under study. In comparison with the particle swarm optimization technique applied to the same back analysis problem, faster convergence of the identified parameters as well as high robustness with respect to the choice of the initial parameter values have been observed. © 2013 Elsevier Ltd.

In this paper, we have considered the problem of optimal actuator and sensor placement for active large flexible structures and proposed a placement optimization method, which is based on balanced reduced models. It overcomes disadvantages arising from demanding numeric procedures related with high order structural models. Optimization procedure relies on H2 and H ∞ norms, as well as on controllability and observability Gramians, which are related to structural eigenmodes of interest. Suggested methods for calculating approximate norms are advantageous due to their feasibility with large structures, where exact calculation of norms would cause numeric problems. A rule for determining optimal actuator/sensor placement in relation with actuation load modeling has been derived and proven by examples. The optimization procedure was documented by several examples showing a good agreement between the results obtained using different placement indices. © 2013 Elsevier Ltd.

This paper gives sufficient conditions for the practical and finite time stability of linear singular continuous time delay systems of the form E x(k +1) = A 0x(k ) + A 1x(k - 1). When we consider finite time stability concept, these new, delay independent conditions are derived using approach based on Lyapunov - like functions and their properties on sub-space of consistent initial conditions.. © 2012 IEEE.

Mechanical lightweight structures often tend to unwanted vibrations due to disturbances. Passive methods for increasing the structural damping are often inadequate for the vibration suppression, since they include additional mass in the form of damping materials, additional stiffening designs or mass damper. In this paper the concept of an active vibration control for piezoelectric light weight structures is introduced and presented through several subsequent steps: model identification, controller design, simulation, experimental verification and implementation on a particular object-piezoelectric smart cantilever beam. Special attention is paid to experimental testing and verification of the results obtained through simulations. The efficiency of the modeling procedure through the subspace-based system identification along with the efficiency of the designed optimal controller are proven based on the experimental verification, which results in vibration suppression to a very high extent not only in comparison with the uncontrolled case, but also in comparison with previously achieved results. The experimental work demonstrates a very good agreement between simulations and experimental results. © 2012 Springer Science+Business Media, LLC.

This paper presents the results of the structural behavior analysis, which was performed using a special type of the user defined finite element incorporated within commercial finite element software. As a basis for the user element implementation, a Mindlin-type nine-node shell element is used, which was developed for the application with piezoelectric materials and composite structures. For the element implementation purposes the FORTRAN user subroutine was developed and incorporated within the ABAQUS finite element software. The analysis is conducted through several examples regarding the piezoelectric bimorph cantilever beam. Results of the analysis document a very good agreement between the user element and analytical and other standard results, confirming thus a successful implementation of the developed user element subroutine. Furthermore, the analysis was extended to show the robustness of the user element to mesh distortion. © 2011 Elsevier B.V. All rights reserved.

The article provides sufficient conditions for the practical and finite time stability of linear singular continuous time delay systems fulfilling the following formulation: Ex(k+1)=A 0x(k)+A 1x(k-1). Analyzing the finite time stability concept, novel delay independent conditions have been presented. The conditions were derived using the linear matrix inequality (LMI) approach. The LMI method was based on the analysis of the Lyapunov-like functions and their properties within the subspace of consistent initial conditions. A novel sufficient delay-dependent criterion for the finite time stability based on the LMI approach has been established. © 2012 IEEE.

This paper provides sufficient conditions for both practical stability and finite time stability of linear singular continuous time delay systems which can be mathematically described as Ex(t) = A 0x(t) + A 1x(t ). Considering a finite time stability concept, new delay independent conditions have been derived using the approach based on the Lyapunov-like functions and their properties on the subspace of consistent initial conditions. These functions do not need to have the properties of positivity in the whole state space and negative derivatives along the system trajectories. When the practical stability has been analyzed the above mentioned approach was combined and supported by the classical Lyapunov technique to guarantee the attractivity property of the system behavior. © 2011 IEEE.

This paper gives sufficient conditions for the practical and finite time stability of a particular class of linear discrete time delay systems. Analyzing the finite time stability concept, these new delay-independent conditions are derived using an approach based on the Lyapunov-like functions. The practical stability and attractive practical stability for discrete time delay systems have been investigated. The above mentioned approach was supported by the classical Lyapunov technique to guarantee the attractivity properties of the system behavior. © 2011 IEEE.

This paper gives sufficient conditions for the practical and finite time stability of linear continuous time delay systems of the form X(t)A 0X(t)A1X(t-T). When we consider finite time stability, these new, delay independent conditions are derived using the approach based on Lyapunov-Krassovski functionals. In this case these functionals need not to have: a) properties of positivity in whole state space and b) negative derivatives along system trajectories. When we consider practical stability, before mentioned concept of stability, it is combined and supported by classical Lyapunov technique to guarantee attractivity properties of system behavior. © 2011 IEEE.

The article provides sufficient conditions for both practical and finite time stability of linear continuous time delay systems described as X(t) A 0X(t)+A1X(t-τ). Considering a finite time stability concept, the new delay independent conditions have been derived using the approach based on the Lyapunov-like functions. These functions do not need to have the properties of positivity in the whole state space and negative derivatives along the system trajectories. When the practical stability has been analyzed the above mentioned approach was combined and supported by the classical Lyapunov technique to guarantee the attractivity property of the system behavior. © 2011 IEEE.

In this article the sufficient conditions for the practical and finite-time stability of the linear continuous systems with the time-delay are presented. The new delay-independent stability conditions are derived using Lyapunov-like functions for the finite-time systems. For these functions it is not necessary to have properties of positivity in the whole state space as well as negative derivatives along the system trajectories. The proposed approach is supported and combined with classical Lyapunov technique to guarantee actractivity of the system. ©2010 IEEE.