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              Event-Triggered Tracking Control for a Class of Nonlinear Systems With Observer and Prescribed Performance

              YOU Xing-Xing YANG Dao-Wen GUO Bin LIU Kai DIAN Song-Yi ZHU Yu-Qi

              游星星, 楊道文, 郭斌, 劉凱, 佃松宜, 朱雨琪. 基于觀測器和指定性能的非線性系統事件觸發跟蹤控制. 自動化學報, 2021, 45(x): 1?14 doi: 10.16383/j.aas.c210387
              引用本文: 游星星, 楊道文, 郭斌, 劉凱, 佃松宜, 朱雨琪. 基于觀測器和指定性能的非線性系統事件觸發跟蹤控制. 自動化學報, 2021, 45(x): 1?14 doi: 10.16383/j.aas.c210387
              You Xing-Xing, Yang Dao-Wen, Guo Bin, Liu Kai, Dian Song-Yi, Zhu Yu-Qi. Event-triggered tracking control for a class of nonlinear systems with observer and prescribed performance. Acta Automatica Sinica, 2021, 45(x): 1?14 doi: 10.16383/j.aas.c210387
              Citation: You Xing-Xing, Yang Dao-Wen, Guo Bin, Liu Kai, Dian Song-Yi, Zhu Yu-Qi. Event-triggered tracking control for a class of nonlinear systems with observer and prescribed performance. Acta Automatica Sinica, 2021, 45(x): 1?14 doi: 10.16383/j.aas.c210387

              基于觀測器和指定性能的非線性系統事件觸發跟蹤控制

              doi: 10.16383/j.aas.c210387

              Event-Triggered Tracking Control for a Class of Nonlinear Systems With Observer and Prescribed Performance

              Funds: Supported by National Key R&D Program of China (2018YFB1307401), National Natural Science Foundation of China under Grant (61906023), Scientific and Technical Programs of Sichuan Province of China (2021YJ0092), Natural Science Foundation of Chongqing Municipality of China (cstc2019jcyj-msxmX0722; cstc2019jcyj-msxmX0710)
              More Information
                Author Bio:

                YOU Xing-Xing Ph. D. candidate at the College of Electrical Engineering from Sichuan University. He received his MS degrees from Chongqing Jiaotong University in 2020. His research interests include the stability theory of neural network, adaptive control of nonlinear systems and its application

                YANG Dao-Wen His research interests include machine vision, perception, artificial intelligence and big data. Corresponding author of this paper

                GUO Bin Associate researcher at the College of Electrical Engineering, Sichuan University. He received his Ph.D degree from University of Electronic Science and Technology in 2020. His research interests include fault diagnosis-fault-tolerant control, cyber-physical fusion system, predictive control and robust control

                LIU Kai Professor at the College of Electrical Engineering, Sichuan University. He received his B.S. and M.S. degrees in computer science from Sichuan University, China, in 1996 and 2001, and his Ph.D. in electrical engineering from the University of Kentucky, USA in 2010. His research interests include computer/machine vision, active/passive stereo vision, and image processing

                DIAN Song-Yi Professor at the College of Electrical Engineering, Sichuan University. He received his Bachelor and MS degrees of Control Engineering from Sichuan University, China in 1996 and 2002, respectively. He received his Ph.D degree in Nanomechanics Engineering from Tohoku University, Japan in 2009. His current research interests include advanced control methods and intelligent signal processing, power-electronics system and its control, motion control and robotic control

                ZHU Yu-Qi Master student at the Electrical Engineering, Sichuan University. His research interests include modeling and motion control for soft robots, disturbance-rejection control

              • 摘要: 針對一類具有外部擾動的非線性系統, 本文提出了一種自適應模糊跟蹤控制方法. 首先, 利用模糊邏輯系統逼近系統未知的非線性函數, 并設計了一個模糊狀態觀測器來估計系統的不可測狀態. 其次, 通過指定性能函數, 使系統的跟蹤誤差能夠約束在指定范圍內. 然后, 利用Backsteping方法結合包含對數函數的Lyapunov泛函, 設計了一個基于事件觸發條件的自適應模糊控制器. 基于Lyapunov穩定性理論和$\tanh$函數的性質證明了所提出的控制策略能夠保證閉環系統中所有信號是半全局一致最終有界的. 最后, 通過一個數值仿真例子驗證了所提出方法的有效性.
              • 圖  1  帶齒輪連接的單連桿機械手

                Fig.  1  Single-link robot arm with a gearing connection

                圖  3  參考信號${y}_{d}$和不同方法下的系統狀態$z_{1}$

                Fig.  3  Reference signal${y}_{d}$and system states$z_{1}$ under different methods

                圖  2  不同方法下的系統跟蹤誤差$\bar{s}_{1}$

                Fig.  2  System tracking errors$\bar{s}_{1}$under different methods

                圖  4  參考信號${\dot{y}}_{d}$和不同方法下的系統狀態$z_{2}$

                Fig.  4  Reference signal${\dot{y}}_{d}$and system states$z_{2}$ under different methods

                圖  5  系統輸出$y = z_{1}$和觀測狀態$\hat{z}_{1}$

                Fig.  5  System output$y = z_{1}$and observed state$\hat{z}_{1}$

                圖  6  系統狀態$z_{2}$和觀測狀態$\hat{z}_{2}$

                Fig.  6  System state$z_{2}$and observed state$\hat{z}_{2}$

                圖  7  自適應律$\|{{\boldsymbol{ \vartheta}}}_{1}\|$$\|{{\boldsymbol{ \vartheta}}}_{2}\|$

                Fig.  7  Adaptive laws$\|{{\boldsymbol{ \vartheta}}}_{1}\|$and$\|{{\boldsymbol{ \vartheta}}}_{2}\|$

                圖  8  不同采樣策略下的控制信號

                Fig.  8  Control signals under different sampling strategies

                圖  9  事件觸發間隔和觸發次數

                Fig.  9  Event trigger interval and number of triggers

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                      1. [1] Martin J. Corless G L. Continuous state feedback guaranteeing uniform ultimate boundedness for uncertain dynamic systems. IEEE Transactions on Automatic Control, 1981, 26(5): 1139-1144 doi: 10.1109/TAC.1981.1102785
                        [2] Wang Xin-Hua, Chen Zeng-Qiang, Yuan Zhu-Zhi. Output tracking based on extended observer for nonlinear uncertain systems. Control and Decision, 2004, 19(10): 1113-1116 doi: 10.3321/j.issn:1001-0920.2004.10.008
                        [3] Cai Z, Dequeiroz M S, Dawson D M. Robust adaptive asymptotic tracking of nonlinear systems with additive disturbance. IEEE Transactions on Automatic Control, 2006, 51(3): 524-529 doi: 10.1109/TAC.2005.864204
                        [4] Pan H H, Chang X P, Zhang D. Event-triggered adaptive control for uncertain constrained nonlinear systems with its application. IEEE Transactions on Industrial Informatics, 2020, 16(6): 3818-3827 doi: 10.1109/TII.2019.2929748
                        [5] Xing L T, Wen C Y, Liu Z T, Su H Y, Cai J P. Event-triggered adaptive control for a class of uncertain nonlinear systems. IEEE Transactions on Automatic Control, 2017, 62(4): 2071-2076 doi: 10.1109/TAC.2016.2594204
                        [6] Wang W, Tong S. Distributed adaptive fuzzy event-triggered containment control of nonlinear strict-feedback systems. IEEE Transactions on Cybernetics, 2020, 50(9): 3973-3983 doi: 10.1109/TCYB.2019.2917078
                        [7] Su X H, Liu Z, Lai G Y, Zhang Y, Chen C L P. Event-triggered adaptive fuzzy control for uncertain strict-feedback nonlinear systems with guaranteed transient performance. IEEE Transactions on Fuzzy Systems, 2019, 27(12): 2327-2337 doi: 10.1109/TFUZZ.2019.2898156
                        [8] Wang J H, Liu Z, Chen C L P, Zhang Y. Event-triggered fuzzy adaptive compensation control for uncertain stochastic nonlinear systems with given transient specification and actuator failures. Fuzzy Sets and Systems, 2019, 365: 1-21 doi: 10.1016/j.fss.2018.04.013
                        [9] Wang Min, Huang Long-Wang, Yang Chen-Guang. Event-triggered adaptive critic fault-tolerant control for a class of discrete-time MIMO systems. Acta Automatica Sinica, 2021, DOI: 10.16383/j.aas.c200721
                        [10] Bechlioulis C P, Rovithakis G A. A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems. Automatica, 2014, 50(4): 1217-1226 doi: 10.1016/j.automatica.2014.02.020
                        [11] Si Wen-Jie, Wang Cong, Zeng Wei. Observed-based adaptive neural tracking control for nonlinear systems with unknown dead-zone. Control and Decision, 2017, 32(5): 780-788
                        [12] Yang Bin, Zhou Qi, Cao Liang, Lu Ren-Quan. Event-triggered control for multi-agent systems with prescribed performance and full state constraints. Acta Automatica Sinica, 2019, 45(08): 1527-1535
                        [13] Qiu J B, Sun K K, Wang T, Gao H J. Observer-based fuzzy adaptive event-triggered control for pure-feedback nonlinear systems with prescribed performance. IEEE Transactions on Fuzzy Systems, 2019, 27(11): 2152-2162 doi: 10.1109/TFUZZ.2019.2895560
                        [14] Qiu J B, Wang T, Sun K K, Rudas I J, Gao H J. Disturbance observer-based adaptive fuzzy control for strict-feedback nonlinear systems with finite-time prescribed performance. IEEE Transactions on Fuzzy Systems, 2021, DOI: 10.1109/TFUZZ.2021.3053327
                        [15] Fischer N, Dani A, Sharma N, Dixon W E. Saturated control of an uncertain nonlinear system with input delay. Automatica, 2013, 49(6): 1741-1747 doi: 10.1016/j.automatica.2013.02.013
                        [16] Zhang Hua-Guang, Zhang Xin, Luo Yan-Hong, Yang Jun. An overview of research on adaptive dynamic programming. Acta Automatica Sinica, 2013, 39(4): 303-311 doi: 10.1016/S1874-1029(13)60031-2
                        [17] Sun Z Y, Zhang C H, Wang Z. Adaptive disturbance attenuation for generalized high-order uncertain nonlinear systems. Automatica, 2017, 80: 102-109 doi: 10.1016/j.automatica.2017.02.036
                        [18] Li D, Pan Z, Deng H, Hu L Y. Adaptive path following controller of a multi-joint snake robot based on the improved serpenoid curve. IEEE Transactions on Industrial Electronics, 2021, DOI: 10.1109/TIE.2021.3075851
                        [19] Deng H, Krsti? M. Stochastic nonlinear stabilization-I: A backstepping design. Systems & Control Letters. 1997, 32(3): 143−150
                        [20] Li Y X, Yang G H. Adaptive neural control of pure-feedback nonlinear systems with event-triggered communications. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(12): 6242-6251 doi: 10.1109/TNNLS.2018.2828140
                        [21] Wang Tong, Qiu Jian-Bin, Gao Hui-Jun. Event-triggered adaptive neural network control for a class of stochastic nonlinear systems. Acta Automatica Sinica, 2019, 45(01): 226-233
                        [22] Zhang C H, Yang G H. Event-triggered adaptive output feedback control for a class of uncertain nonlinear systems with actuator failures. IEEE Transactions on Cybernetics, 2020, 50(1): 201-210 doi: 10.1109/TCYB.2018.2868169
                        [23] Zhou Q, Shi P, Xu S. Adaptive output-feedback fuzzy tracking control for a class of nonlinear systems. IEEE Transactions on Fuzzy Systems, 2011, 19(5): 972-982 doi: 10.1109/TFUZZ.2011.2158652
                        [24] Huang L T, Li Y M, Tong S C. Fuzzy adaptive output feedback control for MIMO switched nontriangular structure nonlinear systems with unknown control directions. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 50(2): 550-564 doi: 10.1109/TSMC.2017.2778099
                        [25] Cao L, Li H Y, Wang N, Zhou Q. Observer-based event-triggered adaptive decentralized fuzzy control for nonlinear large-scale systems. IEEE Transactions on Fuzzy Systems, 2019, 27(6): 1201-1214 doi: 10.1109/TFUZZ.2018.2873971
                        [26] Tong S C, Li Y M, Feng G, Li T S. Observer-based adaptive fuzzy backstepping dynamic surface control for a class of MIMO nonlinear systems. IEEE Transactions on Systems, Man and Cybernetics, Part B, Cybernetics, 2011, 41(4): 1124-1135 doi: 10.1109/TSMCB.2011.2108283
                        [27] Tong S C, Min X, Li Y. Observer-based adaptive fuzzy tracking control for strict-feedback nonlinear systems with unknown control gain functions. IEEE Transactions on Cybernetics, 2020, 50(9): 3903-3913 doi: 10.1109/TCYB.2020.2977175
                        [28] Wang W, Tong S. Adaptive fuzzy bounded control for consensus of multiple strict-feedback nonlinear systems. IEEE Transactions on Cybernetics, 2018, 48(2): 522-531 doi: 10.1109/TCYB.2016.2645763
                        [29] Zhang L L, Yang G H. Adaptive fuzzy prescribed performance control of nonlinear systems with hysteretic actuator nonlinearity and faults. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018, 48(12): 2349-2358 doi: 10.1109/TSMC.2017.2707241
                        [30] Wang L, Basin M V, Li H, Lu R Q. Observer-based composite adaptive fuzzy control for nonstrict-feedback systems with actuator failures. IEEE Transactions on Fuzzy Systems. 2018, 26(4): 2336-2347 doi: 10.1109/TFUZZ.2017.2774185
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                        • 收稿日期:  2021-05-07
                        • 錄用日期:  2021-11-02
                        • 網絡出版日期:  2021-11-28

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