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      Validation of model-based adaptive control method for real-time hybrid simulation

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      https://www.riss.kr/link?id=A108545788

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Real-time hybrid simulation (RTHS) is an effective experimental technique for structural dynamic assessment. However, time delay causes displacement de-synchronization at the interface between the numerical and physical substructures, negatively affecting the accuracy and stability of RTHS. To this end, the authors have proposed a model-based adaptive control strategy with a Kalman filter (MAC-KF). In the proposed method, the time delay is mainly mitigated by a parameterized feedforward controller, which is designed using the discrete inverse model of the control plant and adjusted using the KF based on the displacement command and measurement. A feedback controller is employed to improve the robustness of the controller. The objective of this study is to further validate the power of dealing with a nonlinear control plant and to investigate the potential challenges of the proposed method through actual experiments. In particular, the effect of the order of the feedforward controller on tracking performance was numerically investigated using a nonlinear control plant; a series of actual RTHS of a frame structure equipped with a magnetorheological damper was performed using the proposed method. The findings reveal significant improvement in tracking accuracy, demonstrating that the proposed method effectively suppresses the time delay in RTHS. In addition, the parameters of the control plant are timely updated, indicating that it is feasible to estimate the control plant parameter by KF. The order of the feedforward controller has a limited effect on the control performance of the MAC-KF method, and the feedback controller is beneficial to promote the accuracy of RTHS.
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      Real-time hybrid simulation (RTHS) is an effective experimental technique for structural dynamic assessment. However, time delay causes displacement de-synchronization at the interface between the numerical and physical substructures, negatively affec...

      Real-time hybrid simulation (RTHS) is an effective experimental technique for structural dynamic assessment. However, time delay causes displacement de-synchronization at the interface between the numerical and physical substructures, negatively affecting the accuracy and stability of RTHS. To this end, the authors have proposed a model-based adaptive control strategy with a Kalman filter (MAC-KF). In the proposed method, the time delay is mainly mitigated by a parameterized feedforward controller, which is designed using the discrete inverse model of the control plant and adjusted using the KF based on the displacement command and measurement. A feedback controller is employed to improve the robustness of the controller. The objective of this study is to further validate the power of dealing with a nonlinear control plant and to investigate the potential challenges of the proposed method through actual experiments. In particular, the effect of the order of the feedforward controller on tracking performance was numerically investigated using a nonlinear control plant; a series of actual RTHS of a frame structure equipped with a magnetorheological damper was performed using the proposed method. The findings reveal significant improvement in tracking accuracy, demonstrating that the proposed method effectively suppresses the time delay in RTHS. In addition, the parameters of the control plant are timely updated, indicating that it is feasible to estimate the control plant parameter by KF. The order of the feedforward controller has a limited effect on the control performance of the MAC-KF method, and the feedback controller is beneficial to promote the accuracy of RTHS.

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      참고문헌 (Reference)

      1 Thomas Simpson, "Towards Data-Driven Real-Time Hybrid Simulation: Adaptive Modeling of Control Plants" Frontiers Media SA 6 : 2020

      2 A. Blakeborough, "The development of real–time substructure testing" The Royal Society 359 (359): 1869-1891, 2001

      3 A. P. Darby, "Stability and Delay Compensation for Real-Time Substructure Testing" American Society of Civil Engineers (ASCE) 128 (128): 1276-1284, 2002

      4 Liang Huang, "Stability Analysis of Real-Time Hybrid Simulation for Time-Varying Actuator Delay Using the Lyapunov-Krasovskii Functional Approach" American Society of Civil Engineers (ASCE) 145 (145): 2019

      5 Pei-Ching Chen ; Po-Chang Chen, "Robust stability analysis of real-time hybrid simulation considering system uncertainty and delay compensation" 국제구조공학회 25 (25): 719-732, 2020

      6 Ge Ou, "Robust integrated actuator control: experimental verification and real‐time hybrid‐simulation implementation" Wiley 44 (44): 441-460, 2014

      7 Cristóbal Gálmez, "Robust adaptive model‐based compensator for the real‐time hybrid simulation benchmark" Hindawi Limited 29 (29): 2022

      8 Nikolaos Tsokanas, "Robust Model Predictive Control for Dynamics Compensation in Real-Time Hybrid Simulation" Frontiers Media SA 6 : 2020

      9 Cheng Chen, "Real‐time hybrid simulation with multi‐fidelity Co‐Kriging for global response prediction under structural uncertainties" Wiley 51 (51): 2591-2609, 2022

      10 Juan E. Carrion, "Real-time hybrid testing using model-based delay compensation" 테크노프레스 4 (4): 809-828, 2008

      1 Thomas Simpson, "Towards Data-Driven Real-Time Hybrid Simulation: Adaptive Modeling of Control Plants" Frontiers Media SA 6 : 2020

      2 A. Blakeborough, "The development of real–time substructure testing" The Royal Society 359 (359): 1869-1891, 2001

      3 A. P. Darby, "Stability and Delay Compensation for Real-Time Substructure Testing" American Society of Civil Engineers (ASCE) 128 (128): 1276-1284, 2002

      4 Liang Huang, "Stability Analysis of Real-Time Hybrid Simulation for Time-Varying Actuator Delay Using the Lyapunov-Krasovskii Functional Approach" American Society of Civil Engineers (ASCE) 145 (145): 2019

      5 Pei-Ching Chen ; Po-Chang Chen, "Robust stability analysis of real-time hybrid simulation considering system uncertainty and delay compensation" 국제구조공학회 25 (25): 719-732, 2020

      6 Ge Ou, "Robust integrated actuator control: experimental verification and real‐time hybrid‐simulation implementation" Wiley 44 (44): 441-460, 2014

      7 Cristóbal Gálmez, "Robust adaptive model‐based compensator for the real‐time hybrid simulation benchmark" Hindawi Limited 29 (29): 2022

      8 Nikolaos Tsokanas, "Robust Model Predictive Control for Dynamics Compensation in Real-Time Hybrid Simulation" Frontiers Media SA 6 : 2020

      9 Cheng Chen, "Real‐time hybrid simulation with multi‐fidelity Co‐Kriging for global response prediction under structural uncertainties" Wiley 51 (51): 2591-2609, 2022

      10 Juan E. Carrion, "Real-time hybrid testing using model-based delay compensation" 테크노프레스 4 (4): 809-828, 2008

      11 Pei-Ching Chen ; Shiau-Ching Hsu ; You-Jin Zhong ; Shiang-Jung Wang, "Real-time hybrid simulation of smart base-isolated raised floor systems for high-tech industry" 국제구조공학회 23 (23): 91-106, 2019

      12 T. Horiuchi, "Real-time hybrid experimental system with actuator delay compensation and its application to a piping system with energy absorber" Wiley 28 (28): 1121-1141, 1999

      13 Yoichi Mukai, "Real-Time Hybrid Test Using Two-Individual Actuators to Evaluate Seismic Performance of RC Frame Model Controlled by AMD" Frontiers Media SA 6 : 2020

      14 Xiaoshu Gao, "Real-Time Hybrid Simulation with Polynomial Chaos NARX Modeling for Seismic Response Evaluation of Structures Subjected to Stochastic Ground Motions" American Society of Civil Engineers (ASCE) 148 (148): 2022

      15 L.D. Hashan Peiris, "Passivity control with adaptive feed-forward filtering for real-time hybrid tests" Elsevier BV 12 : 100081-, 2020

      16 Safwan Al-Subaihawi, "Online explicit model updating of nonlinear viscous dampers for real time hybrid simulation" Elsevier BV 154 : 107108-, 2022

      17 Zhao, J., "Nonlinear system modeling and velocity feedback compensation for effective force testing" 131 (131): 244-253, 2005

      18 Phillips, B. M., "Model-based feedforward-feedback actuator control for real-time hybrid simulation" 139 (139): 1205-1214, 2013

      19 Cheng Chen, "Improving the inverse compensation method for real‐time hybrid simulation through a dual compensation scheme" Wiley 38 (38): 1237-1255, 2009

      20 J. Condori, "Exploiting Parallel Computing to Control Uncertain Nonlinear Systems in Real-Time" Springer Science and Business Media LLC 44 (44): 735-749, 2020

      21 Amin Maghareh ; Arun Prakash ; Shirley J. Dyke ; Jeffrey F. Rhoads, "Establishing a stability switch criterion for effective implementation of real-time hybrid simulation" 국제구조공학회 14 (14): 1221-1245, 2014

      22 Hakuno, M., "Dynamic destructive test of a cantilever beam, controlled by an analogcomputer" 1969 (1969): 1-9, 1969

      23 Masayoshi Nakashima, "Development of real‐time pseudo dynamic testing" Wiley 21 (21): 79-92, 1992

      24 Weijie Xu, "Data‐driven nonlinear autoregressive with external input model‐based compensation for real‐time testing" Hindawi Limited 29 (29): 2022

      25 Zhao, J., "Considerations for the development of real-time dynamic testing using servo-hydraulic actuation" 32 (32): 1773-1794, 2003

      26 Narutoshi Nakata ; Matthew Stehman, "Compensation techniques for experimental errors in real-time hybrid simulation using shake tables" 국제구조공학회 14 (14): 1055-1079, 2014

      27 F Weber, "Bouc–Wen model-based real-time force tracking scheme for MR dampers" IOP Publishing 22 (22): 045012-, 2013

      28 Christian E. Silva, "Benchmark control problem for real-time hybrid simulation" Elsevier BV 135 : 106381-, 2020

      29 D.P. McCrum, "An overview of seismic hybrid testing of engineering structures" Elsevier BV 118 : 240-261, 2016

      30 Saeid Hayati ; Wei Song, "An optimal discrete-time feedforward compensator for real-time hybrid simulation" 국제구조공학회 20 (20): 483-498, 2017

      31 HongWei Li, "An adaptive sliding mode control system and its application to real‐time hybrid simulation" Hindawi Limited 29 (29): 2021

      32 Zhen Wang ; Guoshan Xu ; Qiang Li ; Bin Wu, "An adaptive delay compensation method based on a discrete system model for real-time hybrid simulation" 국제구조공학회 25 (25): 569-580, 2020

      33 Alejandro Palacio-Betancur, "Adaptive tracking control for real-time hybrid simulation of structures subjected to seismic loading" Elsevier BV 134 : 106345-, 2019

      34 Yunbyeong Chae, "Adaptive time series compensator for delay compensation of servo‐hydraulic actuator systems for real‐time hybrid simulation" Wiley 42 (42): 1697-1715, 2013

      35 Amirali Najafi, "Adaptive model reference control method for real-time hybrid simulation" Elsevier BV 132 : 183-193, 2019

      36 N. Tsokanas, "Adaptive model predictive control for actuation dynamics compensation in real-time hybrid simulation" Elsevier BV 172 : 104817-, 2022

      37 Fermandois, G. A., "Adaptive Compensation with Magnetorheological Dampers in RTHS Testing" 2021

      38 Salvatore Strano, "Actuator dynamics compensation for real-time hybrid simulation: an adaptive approach by means of a nonlinear estimator" Springer Science and Business Media LLC 85 (85): 2353-2368, 2016

      39 Reza Mirza Hessabi, "A new tracking error-based adaptive controller for servo-hydraulic actuator control" SAGE Publications 22 (22): 2824-2840, 2014

      40 Toshihiko Horiuchi, "A new method for compensating actuator delay in real–time hybrid experiments" The Royal Society 359 (359): 1893-1909, 2001

      41 Xizhan Ning ; Wei Huang ; Guoshan Xu ; Zhen Wang ; Lichang Zheng, "A model-based adaptive control method for real-time hybrid simulation" 국제구조공학회 31 (31): 437-454, 2023

      42 Nikolaos Tsokanas, "A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures" Frontiers Media SA 7 : 2021

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