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非线性系统的2自由度VRFT控制器设计
引用本文:唐小军,王建宏,王新长,易华.非线性系统的2自由度VRFT控制器设计[J].井冈山大学学报(自然科学版),2018(1):5-11.
作者姓名:唐小军  王建宏  王新长  易华
作者单位:井冈山大学数理学院;景德镇陶瓷大学机电学院
基金项目:江西省自然科学基金项目(20161BAB201017);井冈山大学博士科研启动项目(JZB17002)
摘    要:针对非线性系统的复杂性,提出了由非线性前馈控制器与线性反馈控制器构成的2自由度控制器设计。通过设计虚拟参考信号,将非线性前馈控制器的设计转化为非线性函数在某类基函数展开式下的参数辨识;在此基础上,增加一线性控制器于反馈回路用以增强系统的跟踪性能,采用递推最小二乘法辨识线性控制器参数。对闭环系统的稳定性进行了理论分析,给出跟踪误差的上界;最后进行了仿真验证。

关 键 词:非线性  虚拟信号  基函数  最小二乘法
收稿时间:2017/4/17 0:00:00
修稿时间:2017/9/24 0:00:00

TWO DEGREE OF FREEDOMVRFT CONTROLLERS DESIGN METHOD OF NONLINEAR SYSTEM
TANG Xiao-jun,WANG Jian-hong,WANG Xin-chang and YI Hua.TWO DEGREE OF FREEDOMVRFT CONTROLLERS DESIGN METHOD OF NONLINEAR SYSTEM[J].Journal of Jinggangshan University(Natural Sciences Edition),2018(1):5-11.
Authors:TANG Xiao-jun  WANG Jian-hong  WANG Xin-chang and YI Hua
Institution:School of Mathematics and Physics, Jinggangshan University, Ji''an, Jiangxi 343009, China,School of Mechanical and Electronic Engineering, Jingdezhen Ceramic university, Jingdezhen, Jiangxi 333403, China,School of Mathematics and Physics, Jinggangshan University, Ji''an, Jiangxi 343009, China and School of Mathematics and Physics, Jinggangshan University, Ji''an, Jiangxi 343009, China
Abstract:In view of the complex dynamic characteristics of the nonlinear system, a design method of the two degrees of freedom controller is proposed. Designing the nonlinear feed forward part of the two degrees of freedom controller is transformed into a series expansion of nonlinear functions with basic functions multiplied by parameters and parameter identification using the design of virtual reference signal. Furthermore, we add a linear controller part in a feedback loop to enhance the tracking performance of the system, and use the recursive least squares identification method to identify the parameters of the linear controller. The stability of the closed-loop system are theoretically analyzed, and the value of the upper bound of the tracking error is given. Finally, simulation results are shown.
Keywords:nonlinear  virtual signal  basis functions  the Least Square method
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