Adaptive Implicit Inverse Control for a Class of Discrete-Time Hysteretic Nonlinear Systems and Its Application

被引:38
|
作者
Zhang, Xiuyu [1 ]
Li, Bin [1 ]
Chen, Xinkai [2 ]
Li, Zhi [3 ]
Peng, Yaxuan [1 ]
Su, Chun-Yi [4 ]
机构
[1] Northeast Elect Power Univ, Sch Automat Engn, Changchun 132012, Jilin, Peoples R China
[2] Shibaura Inst Technol, Dept Elect & Informat Syst, Saitama 3378570, Japan
[3] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
[4] Concordia Univ, Dept Mech & Ind Engn, Montreal, PQ H3G 1M8, Canada
基金
日本学术振兴会; 中国国家自然科学基金;
关键词
Hysteresis; Nonlinear systems; Adaptive systems; IEEE transactions; Mechatronics; Control systems; Backstepping; Adaptive control; discrete time; dynamic surface control; hysteresis nonlinearities; OUTPUT-FEEDBACK CONTROL; PREDICTIVE CONTROL; NEURAL-NETWORK; NN CONTROL; DESIGN;
D O I
10.1109/TMECH.2020.2991666
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article proposes an adaptive implicit inverse control scheme for a class of discrete-time hysteretic nonlinear systems. The Prandtl-Ishlinskii model is employed to characterize the hysteresis loop in piezoelectric actuator. The main contributions are as follows: 1) by using the dynamic surface control technique, which introduces the digital first-order low-pass filter, the original control system are not required to be transformed into an unknown special form; 2) the hysteresis implicit inverse compensator is constructed to overcome the hysteresis, which implies that the hysteresis item coupled with control signal is treated as the temporary control signal from which the method of searching the approximately control signal is designed; and 3) by employing the experimental platform of the piezoelectric positioning stage, the experimental verifications of the designed discrete-time adaptive controller are implemented. It is proved that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded and the experimental results show the effectiveness of the proposed adaptive dynamic surface discrete-time motion control (ADSDMC) scheme.
引用
收藏
页码:2112 / 2122
页数:11
相关论文
共 50 条
  • [31] Adaptive Neural Digital Control of Hysteretic Systems With Implicit Inverse Compensator and Its Application on Magnetostrictive Actuator
    Zhang, Xiuyu
    Li, Bin
    Li, Zhi
    Yang, Chenguang
    Chen, Xinkai
    Su, Chun-Yi
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 33 (02) : 667 - 680
  • [32] Adaptive Optimal Control for Nonlinear Discrete-Time Systems
    Qin, Chunbin
    Zhang, Huaguang
    Luo, Yanhong
    PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON ADAPTIVE DYNAMIC PROGRAMMING AND REINFORCEMENT LEARNING (ADPRL), 2013, : 13 - 18
  • [33] Adaptive Kriging control of discrete-time nonlinear systems
    Wu, H.
    Sun, F.
    IET CONTROL THEORY AND APPLICATIONS, 2007, 1 (03): : 646 - 656
  • [34] A new adaptive scheme for a class of discrete-time nonlinear systems
    González, GA
    JOURNAL OF PROCESS CONTROL, 2001, 11 (01) : 13 - 17
  • [35] Adaptive discrete-time fault diagnosis for a class of nonlinear systems: Application to a mechanical manipulator
    Antonelli, G
    Caccavale, F
    Villani, L
    PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL, 2003, : 667 - 672
  • [36] Output feedback adaptive control of a class of nonlinear discrete-time systems with unknown control directions
    Yang, Chenguang
    Ge, Shuzhi Sam
    Lee, Tong Heng
    AUTOMATICA, 2009, 45 (01) : 270 - 276
  • [37] Event-triggered Adaptive Control for a Class of Discrete-time Uncertain Nonlinear Systems
    Zhuang, Wenxiu
    Wen, Changyun
    Wang, Lei
    Liu, Zhitao
    Su, Hongye
    PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 2282 - 2287
  • [38] Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems
    Ge, SS
    Li, GY
    Lee, TH
    AUTOMATICA, 2003, 39 (05) : 807 - 819
  • [39] Adaptive Predictive Control of a Class of Discrete-Time MIMO Nonlinear Systems with Uncertain Couplings
    Yang, Chenguang
    Li, Yanan
    Ge, Shuzhi Sam
    Lee, Tong Heng
    2010 AMERICAN CONTROL CONFERENCE, 2010, : 2428 - 2433
  • [40] Adaptive neural network control for a class of MIMO nonlinear systems with disturbances in discrete-time
    Ge, SS
    Zhang, J
    Lee, TH
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (04): : 1630 - 1645