• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2017, Vol. 53 ›› Issue (22): 109-116.doi: 10.3901/JME.2017.22.109

• 运载工程 • 上一篇    下一篇

一类施加单向控制量的不确定非线性系统的重复学习控制

孙友刚1, 李万莉1, 吉文2   

  1. 1. 同济大学机械与能源工程学院 上海 201804;
    2. 同济大学国家磁浮交通工程技术研究中心 上海 201306
  • 收稿日期:2016-11-28 修回日期:2017-06-05 出版日期:2017-11-20 发布日期:2017-11-20
  • 通讯作者: 孙友刚(通信作者),男,1989年出生,博士研究生。主要研究方向为非线性动力学及控制。E-mail:1989yoga@tongji.edu.cn
  • 作者简介:李万莉,女,1965年出生,博士,教授,博士研究生导师。主要研究方向为工程机械智能控制、磁悬浮理论及控制。E-mail:cnlwl@tongji.edu.cn
  • 基金资助:
    国家科技支撑计划(2013BAG19B00-01)和"十二五"国家科技支撑计划(2011BAJ02B00)资助项目。

Repetitive Learning Control for Class of Unidirectional Control Input Systems with Unknown Nonlinear Dynamics

SUN Yougang1, LI Wanli1, JI Wen2   

  1. 1. School of Mechanical Engineering, Tongji University, Shanghai 201804;
    2. National Maglev Transportation Engineering R & D Center, Tongji University, Shanghai 201306
  • Received:2016-11-28 Revised:2017-06-05 Online:2017-11-20 Published:2017-11-20

摘要: 针对存在有界的、周期变化的非线性不确定动态的二阶系统,提出一种使系统渐近地跟踪目标轨迹的控制律。考虑仅能施加单向控制量的系统,所提出的控制律利用饱和函数和基于在线学习的估计器相结合来学习和估计未知非线性动态特性,并对未知动态进行补偿以保证系统跟踪误差渐近收敛于零。同时引入自适应陷波滤波器(Adaptive notch filter,ANF)来在线估计未知非线性动态特性的频率。不同于以前的方法,提出的基于ANF的饱和改进型重复控制律只需要未知动态特性是有界的(未知动态特性的结构、参数、频率是不需要预先知道的)。最后将此控制律应用到只能提供竖直向上电磁力的EMS型磁悬浮系统中,设计出适合磁悬浮系统的控制策略。仿真结果证明了所提出的控制策略的有效性。

关键词: 不确定动态, 磁悬浮系统, 非线性控制, 重复学习方法

Abstract: An improved saturated learning-based control law is proposed to deal with a class of unidirectional control input systems to make the systems track the target trajectory asymptotically. Considering the systems with unidirectional control input only, the presented control law utilizes a saturated function and repetitive learning estimator to online learn and estimate the unknown periodic nonlinear dynamics, and compensate for the unknown dynamics to ensure the convergence of the tracking error asymptotically. At the same time, an adaptive notch filter(ANF) is utilized to online estimate frequency of the periodic dynamics in conjunction with the improved saturated learning-based control law. Differing from the previous methods, the presented control law only needs the uncertain dynamics is bounded (the structure, parameters and frequency of the uncertain dynamics is not need to be given beforehand). At last, the presented control law is applied to the electromagnetic suspension system(EMS), which can only provide a vertical upward electromagnetic force. The simulation results are given to demonstrate the effectiveness of the proposed control strategy.

Key words: electromagnetic suspension system, nonlinear control, repetitive learning control, unknown dynamics

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