广东工业大学学报 ›› 2022, Vol. 39 ›› Issue (05): 137-144.doi: 10.12052/gdutxb.220050

• • 上一篇    

基于事件触发的大规模互联非线性系统的自适应分散漏斗控制

杨文静, 夏建伟   

  1. 聊城大学 数学科学学院,山东 聊城 252000
  • 收稿日期:2022-03-16 发布日期:2022-07-18
  • 通信作者: 夏建伟(1978–),男,教授,博士生导师,主要研究方向为时滞系统稳定性分析、随机系统鲁棒控制、非线性系统自适应控制等,E-mail:njustxjw@126.com
  • 作者简介:杨文静(1998–),女,硕士研究生,主要研究方向为非线性系统、自适应控制、反步控制,E-mail:yangwenjing1024@163.com
  • 基金资助:
    国家自然科学基金资助项目(61973148)

Adaptive Decentralized Funnel Control for Large-scale Interconnected Nonlinear Systems Based on Event-triggered

Yang Wen-jing, Xia Jian-wei   

  1. School of Mathematical Science, Liaocheng University, Liaocheng 252000, China
  • Received:2022-03-16 Published:2022-07-18

摘要: 研究了一类不确定大规模非线性系统的分散自适应事件触发漏斗控制问题。首先,利用一个新的带有障碍李雅普诺夫函数的漏斗控制方法,构造了一种自适应分散漏斗控制器,以实现给定瞬态行为的输出跟踪。其次,为了解决控制器设计中的互联项问题,引入了一个辅助非线性函数。同时,将命令滤波技术应用到反步设计中,避免了反步过程中的“复杂性爆炸”问题。此外,还设计了一种事件触发机制,以减少控制器和执行器之间不必要的传输,从而提高资源效率。结果表明,所提出的控制方案能保证闭环系统的所有信号都是有界的,并且跟踪误差总是在漏斗中演化。最后,通过一个数值系统验证了该控制方法的有效性。

关键词: 大规模非线性系统, 漏斗控制, 事件触发控制, 命令滤波技术

Abstract: A decentralized adaptive event-triggered funnel control for a class of uncertain large-scale nonlinear systems is studied. Firstly, a new adaptive decentralized funnel controller was constructed by using a new funnel control method with barrier Lyapunov function to achieve output tracking for a given transient behavior. Secondly, an auxiliary nonlinear function was introduced to solve the interconnection problem in controller design. At the same time, the command filtering technique was applied to backstepping design to avoid ‘complexity explosion’ in backstepping process. In addition, an event-triggered mechanism was designed to reduce unnecessary transfers between controllers and actuators, thus improving resource efficiency. The results show that the proposed control scheme can ensure that all the signals of the closed-loop system are bounded and the tracking error always evolves in the funnel. Finally, the effectiveness of the control method is verified by a numerical system.

Key words: large-scale nonlinear, funnel control, event-triggered control, command filter technology

中图分类号: 

  • TG156
[1] JAIN S, KHORRAMI F. Decentralized adaptive output feedback design for large-scale nonlinear systems [J]. IEEE Transactions on Automatic Control, 1997, 42(5): 729-735.
[2] JIANG Z P. Decentralized and adaptive nonlinear tracking of large-scale systems via output feedback [J]. IEEE Transactions on Automatic Control, 2000, 45(11): 2122-2128.
[3] LIU S J, ZHANG J F, JIANG Z P. Decentralized adaptive output-feedback stabilization for large-scale stochastic nonlinear systems [J]. Automatica, 2007, 43(2): 238-251.
[4] TONG S C, LI Y M, LIU Y J. Observer-based adaptive neural networks control for large-scale interconnected systems with nonconstant control gains [J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(4): 1575-1585.
[5] 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.
[6] GONG J Y, JIANG B, SHEN Q K. Adaptive fault tolerant neural control for large-scale systems with actuator faults [J]. International Journal of Control, Automation and Systems, 2019, 17: 1421-1431.
[7] LI Y M, TONG S C. Fuzzy adaptive control design strategy of nonlinear switched large-scale systems [J]. IEEE Transaction on Systems, Man, and Cybernetics: Systems, 2018, 48(12): 2209-2218.
[8] WANG H Q, PETER LIU X P, ZHAO X D, et al. Adaptive fuzzy finite-time control of nonlinear systems with actuator faults [J]. IEEE Transactions on Cybernetics, 2020, 50(5): 1786-1797.
[9] SUI S, PHILIP CHEN L P, TONG S C. Event-trigger-based finite-time fuzzy adaptive control for stochastic nonlinear system with unmodeled dynamics [J]. IEEE Transactions on Fuzzy Systems, 2021, 29(7): 1914-1926.
[10] LIANG H J, LIU G L, ZHANG G H, et al. Neural-network-based event-triggered adaptive control of nonaffine nonlinear multiagent systems with dynamic uncertainties [J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(5): 2239-2250.
[11] HUANG J S, WANG W, WEN C Y, et al. Adaptive event-triggered control of nonlinear systems with controller and parameter estimator triggering [J]. IEEE Transactions on Automatic Control, 2020, 65(1): 318-324.
[12] MA H, LI H Y, LIANG H J, et al. Adaptive fuzzy event-triggered control for stochastic nonlinear systems with full state constraints and actuator faults [J]. IEEE Transactions on Fuzzy Systems, 2019, 27(11): 2242-2254.
[13] WANG L J, PHILIP CHEN C L. Reduced-order observer-based dynamic event-triggered adaptive NN control for stochastic nonlinear systems subject to unknown input saturation [J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 32(4): 1678-1690.
[14] JI Y H, ZHOU H L, ZONG Q. Decentralized adaptive event-triggered control for nonlinear interconnected systems in strict-feedback form [J]. International Journal of Control, Automation and Systems, 2020, 18(4): 980-990.
[15] BECHLIOULIS C P, ROVITHAKIS G A. Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance [J]. IEEE Transactions on Automatic Control, 2008, 53(9): 2090-2099.
[16] ZHOU Q, LI H Y, WU C W, et al. Adaptive fuzzy control of nonlinear systems with unmodeled dynamics and input saturation using small-gain approach [J]. IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2017, 47(8): 1979-1989.
[17] LI Y M, SHAO X F, TONG S C. Adaptive fuzzy prescribed performance control of nontriangular structure nonlinear systems [J]. IEEE Transactions on Fuzzy Systems, 2020, 28(10): 2416-2426.
[18] ZHANG L L, YANG G H. Adaptive fuzzy prescribed performance control of nonlinear systems with hysteretic actuator nonlinearity and faults [J]. IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2018, 48(12): 2349-2358.
[19] ILCHMANN A, RYAN E P, TOWNSEND P. Tracking with prescribed transient behaviour [J]. ESAIM:Control, Optimisation and Calculus of Variations, 2002, 7: 471-493.
[20] HACKL M C, HOPFE N, ILCHMANN A, et al. Funnel control for systems with relative degree two [J]. SIAM Journal on Control and Optimization, 2013, 51(2): 965-995.
[21] BERGER T, REIS T. Funnel control via funnel precompensator for minimum phase systems with relative degree two [J]. IEEE Transactions on Automatic Control, 2018, 63(7): 2264-2271.
[22] LIBERZON D, TRENN S. The bang-bang funnel controller for uncertain nonlinear systems with arbitrary relative degree [J]. IEEE Transactions on Automatic Control, 2013, 58(12): 3126-3141.
[23] CHOWDHURY D, KHALIL H K. Funnel control for nonlinear systems with arbitrary relative degree using high-gian observers [J]. Automatica, 2019, 105: 107-116.
[24] LIU Y H, SU C Y, LI H Y. Adaptive output feedback funnel control of uncertain nonlinear systems with arbitrary relative degree [J]. IEEE Transactions on Automatic Control, 2021, 66(6): 2854-2860.
[25] SUN Y M, CHEN B, LIN C, et al. Adaptive neural control for a class of stochastic nonlinear systems by backstepping approach [J]. Information Sciences, 2016, 369(10): 748-764.
[26] FARRELL J A, POLYCARPOU M, SHARMA M, et al. Command filtered backstepping [J]. IEEE Transactions on Automatic Control, 2009, 54(6): 1391-1395.
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