Journal of Guangdong University of Technology ›› 2023, Vol. 40 ›› Issue (02): 55-63.doi: 10.12052/gdutxb.210110

Previous Articles     Next Articles

Prescribed Performance Control for a Class of Nonlinear Pure-feedback Systems with Actuator Faults

Qiu Jun-hao, Cheng Zhi-jian, Lin Guo-huai, Ren Hong-ru, Lu Ren-quan   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2021-07-22 Online:2023-03-25 Published:2023-04-07

Abstract: In this paper, considering a class of nonlinear systems with full state constraints and actuator faults, an adaptive neural network output feedback fault-tolerant control algorithm with prescribed performance is proposed. A state observer is constructed to solve the unmeasurable states problem. Unknown nonlinear functions in the systems are approximated by radial basis function neural networks (RBF NNs) . By introducing the nonlinear mapping, the systems with state constraints are transformed into novel systems without state constraints. Moreover, a novel performance function is utilized to guarantee that the tracking error converges within a preset time. Meanwhile, the convergence speed can be adjusted through the parameter design. Finally, it is proved that the control algorithm ensures that all signals in the closed-loop systems are semi-globally uniformly ultimately bounded. The effectiveness of the algorithm is verified by a numerical simulation.

Key words: adaptive neural networks control, actuator faults, full state constraints, prescribed performance, output feedback, dynamic surface control

CLC Number: 

  • TP13
[1] LI H Y, WU Y, CHEN M. Adaptive fault-tolerant tracking control fordiscrete-time multiagent systems via reinforcement learning algorithm [J]. IEEE Transactions on Cybernetics, 2021, 51(3): 1163-1174.
[2] 田为刚, 王银河, 李玉姣. 一类非线性不确定系统的输出跟踪控制[J]. 广东工业大学学报, 2015, 32(1): 91-97.
TIAN W G, WANG Y H, LI Y J. Fuzzy adaptive output tracking control for a class of uncertain nonlinear systems [J]. Journal of Guangdong University of Technology, 2015, 32(1): 91-97.
[3] LIN G H, LI H Y, MA H, et al. Human-in-the-loop consensus control for nonlinear multi-agent systems with actuator faults [J]. IEEE/CAA Journal of Automatica Sinica, 2022, 9(1): 111-122.
[4] MA H, LI H Y, LIANG H J, et al. Adaptive fuzzy event-triggeredcontrol for stochastic nonlinear systems with full state constraints andactuator faults [J]. IEEE Transactions on Fuzzy Systems, 2019, 27(11): 2242-2254.
[5] 郑晓宏, 董国伟, 周琪, 等. 带有输出约束条件的随机多智能体系统容错控制[J]. 控制理论与应用, 2020, 37(5): 961-968.
ZHENG X H, DONG G W, ZHOU Q, et al. Fault-tolerantcontrol for stochastic multi-agent systems with output constraints [J]. Control Theory & Applications, 2020, 37(5): 961-968.
[6] REN H R, KARIMI H R, LU R Q, et al. Synchronization of network systems via aperiodic sampled-data control with constant delay andapplication to unmanned ground vehicles [J]. IEEE Transactions on Industrial Electronics, 2020, 67(6): 4980-4990.
[7] 周琪, 陈广登, 鲁仁全, 等. 基于干扰观测器的输入饱和多智能体系统事件触发控制[J]. 中国科学:信息科学, 2019, 49: 1502-1516.
ZHOU Q, CHEN G D, LU R Q, et al. Disturbance-observer-based event-triggered control for multi-agent systems withinput saturation [J]. Science China Information Sciences, 2019, 49: 1502-1516.
[8] MA H, LI H Y, LU R Q, et al. Adaptive event-triggered control for aclass of nonlinear systems with periodic disturbances [J]. Science ChinaInformation Sciences, 2020, 63(5): 150212.
[9] 曾光, 孙炳达, 梁慧冰. 一种基于神经网络的直接自适应控制器[J]. 广东工业大学学报, 2000, 17(1): 20-23.
ZENG G, SUN B D, LIANG H B. A direct adaptive controller based on neural network [J]. Journal of Guangdong University of Technology, 2000, 17(1): 20-23.
[10] ZHOU Q, ZHAO S Y, LI H Y, et al. Adaptive neural network tracking control for robotic manipulators with dead zone [J]. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(12): 3611-3620.
[11] LI Y M, TONG S C. Adaptive neural networks prescribed performance control design for switched interconnected uncertain nonlinear systems [J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(7): 3059-3068.
[12] REN B B, GE S S, TEE K P, et al. Adaptive neural control for outputfeedback nonlinear systems using a barrier Lyapunov function [J]. IEEE Transactions on Neural Networks, 2010, 21(8): 1339-1345.
[13] ZHANG J X, YANG G H. Prescribed performance fault-tolerant control of uncertain nonlinear systems with unknown control directions [J]. IEEE Transactions on Automatic Control, 2017, 62(12): 6529-6535.
[14] WANG C C, YANG G H. Observer-based adaptive prescribed performance tracking control for nonlinear systems with unknown controldirection and input saturation [J]. Neurocomputing, 2018, 284: 17-26.
[15] KOSTARIGKA A K, ROVITHAKIS G A. Adaptive dynamic output feedback neural network control of uncertain MIMO nonlinearsystems with prescribed performance [J]. IEEE Transactions on Neural Networks and Learning Systems, 2012, 23(1): 138-149.
[16] NI J K, AHN C K, LIU L, et al. Prescribed performance fixed-time recurrent neural network control for uncertain nonlinear systems [J]. Neurocomputing, 2019, 363: 351-365.
[17] 杨彬, 周琪, 曹亮, 等. 具有指定性能和全状态约束的多智能体系统事件触发控制[J]. 自动化学报, 2019, 45(8): 1527-1535.
YANG B, ZHOU Q, CAO L, et al. Event-triggered control formulti-agent systems with prescribed performance and full state constraints [J]. Acta Automatica Sinica, 2019, 45(8): 1527-1535.
[18] 赵广磊, 高儒帅, 陈健楠. 具有执行器故障的四旋翼无人机自适应预定性能控制[J]. 控制与决策, 2021, 36(9): 2103-2112.
ZHAO G L, GAO R S, CHEN J N. Adaptive prescribedperformance control of quadrotor with unknown actuator fault [J]. Control and Decision, 2021, 36(9): 2103-2112.
[19] WANG F, CHEN B, LIN C, et al. Adaptive neural network finite-time output feedback control of quantized nonlinear systems [J]. IEEE Transactions on Cybernetics, 2018, 48(6): 1839-1848.
[20] WANG H H, CHEN B, LIN C, et al. Observer-based adaptive neuralcontrol for a class of nonlinear pure-feedback systems [J]. Neurocomputing, 2016, 171: 1517-1523.
[21] ZHOU Q, SHI P, XU S Y, et al. Observer-based adaptive neural network control for nonlinear stochastic systems with time delay [J]. IEEE Transactionson Neural Networks and Learning Systems, 2013, 24(1): 71-80.
[22] YANG H J, SHI P, ZHAO X D, et al. Adaptive output-feedback neuraltracking control for a class of nonstrict-feedback nonlinear systems [J]. Information Sciences, 2016, 334: 205-218.
[23] AREFIM M, ZAREI J, KARIMI H R. Adaptiveoutput feedback neural network control of uncertain non-affine systems with unknowncontrol direction [J]. Journal of the Franklin Institute, 2014, 351: 4302-4316.
[24] 毛骏, 张天平, 夏晓南, 等. 执行器有故障的多输入单输出系统的自适应输出反馈控制[J]. 控制理论与应用, 2016, 33(4): 512-522.
MAO J, ZHANG T P, XIA X N, et al. Adaptive outputfeedback control for multi-input single-output systems with actuatorfailures [J]. Control Theory & Applications, 2016, 33(4): 512-522.
[25] LI Y M, TONG S C. Adaptive neural networks decentralized FTC design for nonstrict-feedback nonlinear interconnected large-scale systems against actuator faults [J]. IEEE Transactions on Neural Networksand Learning Systems, 2017, 28(11): 2541-2554.
[26] LI D P, LIU Y J, TONG S C, et al. Neural networks-based adaptivecontrol for nonlinear state constrained systems with input delay [J]. IEEE Transactions on Cybernetics, 2019, 49(4): 1249-1258.
[27] BOULKROUNE A. A fuzzy adaptive control approach for nonlinear systems with unknown control gain sign [J]. Neurocomputing, 2016, 179: 318-325.
[28] ZHANG T P, XIA M Z, YI Y. Adaptive neural dynamic surface control of strict-feedback nonlinear systems with full state constraintsand unmodeled dynamics [J]. Automatica, 2017, 81: 232-239.
[29] LIU C G, WANG H Q, LIU X P, et al. Adaptive finite-time fuzzy funnel control for nonaffine nonlinear systems [J]. IEEE Transactions on Systems, Man, And Cybernetics:Systems, 2021, 51(5): 2894-2903.
[1] Meng Qing-xin, Lai Xu-zhi, Yan Ze, Wu Min. Progress and Prospect of Motion Control for the Flexible Manipulator Under the Influence of Actuator Faults [J]. Journal of Guangdong University of Technology, 2022, 39(05): 9-20.
[2] Zhang Lin-chuang, Du Xin-ye, Jin Hong-hong, Zhou Wei, Sun Yong-hui. Asynchronous Control of Mode-constrained Linear Jump Systems with Time-varying Emission Probability [J]. Journal of Guangdong University of Technology, 2022, 39(05): 46-51,60.
[3] Luo Liang,Jin Chao-yong,Chen De-yin,Hu Nan-hui . Output Feedback Stabilization of a Class of Nonlinear Uncertain Time-delay Systems [J]. Journal of Guangdong University of Technology, 2008, 25(1): 20-23.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!