Perturbation observer-based adaptive passive control for nonlinear systems with uncertainties and disturbances

被引:9
作者
Yang, B. [1 ,2 ]
Jiang, L. [2 ]
Zhang, C. K. [2 ,3 ]
Sang, Y. Y. [2 ]
Yu, T. [4 ]
Wu, Q. H. [2 ,4 ]
机构
[1] Kunming Univ Sci & Technol, Fac Elect Power Engn, Kunming, Yunnan, Peoples R China
[2] Univ Liverpool, Dept Elect Engn & Elect, Liverpool L69 3GJ, Merseyside, England
[3] China Univ Geosci, Sch Automat, Wuhan, Hubei, Peoples R China
[4] South China Univ Technol, Sch Elect Power Engn, Guangzhou, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Adaptive passive control; high-gain perturbation observer; uncertain nonlinear system; robustness; DESIGN;
D O I
10.1177/0142331216678313
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a perturbation observer-based adaptive passive control scheme is developed to provide great robustness of nonlinear systems against the unpredictable uncertainties and disturbances therein. The proposed scheme includes a high-gain perturbation observer and a robust passive controller. The high-gain perturbation observer is designed to estimate online the perturbation aggregated from the combinatorial effect of system nonlinearity, parameter uncertainty, unmodelled dynamics and fast time-varying external disturbances. Then the robust passive controller, using the estimated perturbation, can produce the minimal control effort needed to compensate for the magnitude of the actual current perturbation. Furthermore, the convergence of estimation error of the high-gain perturbation observer and the closed-loop system stability are analyzed theoretically. Finally, two practical examples are given to show the effectiveness and advantages of the proposed approach over the accurate model-based passive control scheme and the linearly parametric estimation-based adaptive passive control scheme.
引用
收藏
页码:1223 / 1236
页数:14
相关论文
共 41 条
  • [1] High-gain observers in the presence of measurement noise: A switched-gain approach
    Ahrens, Jeffrey H.
    Khalil, Hassan K.
    [J]. AUTOMATICA, 2009, 45 (04) : 936 - 943
  • [2] [Anonymous], 2002, NONLINEAR SYSTEMS
  • [3] Simple output feedback adaptive control based on passification principle
    Bobtsov, A. A.
    Pyrkin, A. A.
    Kolyubin, S. A.
    [J]. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2014, 28 (7-8) : 620 - 632
  • [4] Output Control of Nonlinear Delay Systems with Unmodeled Dynamics
    Bobtsov, A. A.
    Faronov, M. V.
    [J]. JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL, 2011, 50 (03) : 429 - 437
  • [5] Bobtsov AA, 2005, AUTOMAT REM CONTR+, V66, P108
  • [6] Perturbation Estimation Based Nonlinear Adaptive Control of a Full-Rated Converter Wind Turbine for Fault Ride-Through Capability Enhancement
    Chen, J.
    Jiang, L.
    Yao, Wei
    Wu, Q. H.
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (06) : 2733 - 2743
  • [7] Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities
    Chen, Mou
    Ge, Shuzhi Sam
    How, Bernard Voon Ee
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2010, 21 (05): : 796 - 812
  • [8] Disturbance-Observer-Based Control and Related Methods-An Overview
    Chen, Wen-Hua
    Yang, Jun
    Guo, Lei
    Li, Shihua
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2016, 63 (02) : 1083 - 1095
  • [9] A nonlinear disturbance observer for robotic manipulators
    Chen, WH
    Ballance, DJ
    Gawthrop, PJ
    O'Reilly, J
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2000, 47 (04) : 932 - 938
  • [10] Decentralized sliding mode adaptive controller design based on fuzzy neural networks for interconnected uncertain nonlinear systems
    Da, FP
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2000, 11 (06): : 1471 - 1480