为提高电励磁直线电动机(electrically excited linear motors,EELM)驱动的数控机床磁悬浮平台控制系统的性能,提出一种非线性自适应反步控制方法。研究EELM的结构与运行机理,该EELM的定子由铁心和励磁绕组组成,动子由动子铁心和电枢绕...为提高电励磁直线电动机(electrically excited linear motors,EELM)驱动的数控机床磁悬浮平台控制系统的性能,提出一种非线性自适应反步控制方法。研究EELM的结构与运行机理,该EELM的定子由铁心和励磁绕组组成,动子由动子铁心和电枢绕组组成,与数控机床进给平台固定连接驱动平台运动,励磁磁场对动子铁心的单边磁拉力实现平台的悬浮;建立EELM磁悬浮平台控制系统的数学模型与状态方程;对电励磁直线电动机磁悬浮平台运行过程中存在的不确定性扰动,设计非线性自适应反步控制器,对未知扰动进行估计,采用李雅普诺夫理论证明系统的稳定性;用MATLAB/Simulink对控制系统进行计算机仿真,验证所提方法的有效性。展开更多
A new adaptive Type-2 (T2) fuzzy controller was developed and its potential performance advantage over adaptive Type-1 (T1) fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, th...A new adaptive Type-2 (T2) fuzzy controller was developed and its potential performance advantage over adaptive Type-1 (T1) fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.展开更多
文摘为提高电励磁直线电动机(electrically excited linear motors,EELM)驱动的数控机床磁悬浮平台控制系统的性能,提出一种非线性自适应反步控制方法。研究EELM的结构与运行机理,该EELM的定子由铁心和励磁绕组组成,动子由动子铁心和电枢绕组组成,与数控机床进给平台固定连接驱动平台运动,励磁磁场对动子铁心的单边磁拉力实现平台的悬浮;建立EELM磁悬浮平台控制系统的数学模型与状态方程;对电励磁直线电动机磁悬浮平台运行过程中存在的不确定性扰动,设计非线性自适应反步控制器,对未知扰动进行估计,采用李雅普诺夫理论证明系统的稳定性;用MATLAB/Simulink对控制系统进行计算机仿真,验证所提方法的有效性。
基金Project(51005253) supported by the National Natural Science Foundation of ChinaProject(2007AA04Z344) supported by the National High Technology Research and Development Program of China
文摘A new adaptive Type-2 (T2) fuzzy controller was developed and its potential performance advantage over adaptive Type-1 (T1) fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.