摘要
讨论一类不确定非线性系统的可保证瞬态性能的迭代学习控制问题.引入限定跟踪误差瞬态特性的界函数,通过误差转换方法,定义一个转换误差变量,将跟踪误差的保证瞬态特性问题转化为该误差变量的有界性问题.采用Lyapunov方法,设计迭代学习控制器处理系统中参数和非参数不确定性.并且,采用完全限幅学习机制,保证转换误差变量的有界性和一致收敛性.从而既能得出系统输出在整个作业区间的完全跟踪性能,同时又能够保证跟踪误差在每次迭代的过程中具有保证的瞬态特性.仿真结果验证了所提控制方法的有效性.
For a class of uncertain nonlinear time-varying systems, we present an iterative learning control scheme guar-anteeing transient performance bounds. By introducing an error transformation, we convert the problem of guaranteeingtransient performance of the tracking error to that of ensuring boundedness of the transformed error. Applying Lyapunovsynthesis, we carry out the control design for handling both parametric and nonparametfic uncertainties of system dynam-ics. It is shown that, with the use of fully-saturated learning mechanisms, the system output can completely track the desiredtrajectory over the entire pre-specified time interval as the number of iteration increases, and the tracking error is confinedwithin the transient performance bounds for each iteration cycle, while the boundedness and the uniform convergence of thetransformed error are guaranteed. Simulation results are presented to demonstrate the effectiveness of this learning controlmethod.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2014年第10期1295-1301,共7页
Control Theory & Applications
基金
国家自然科学基金资助项目(61174034
61374103)
关键词
收敛性
迭代学习控制
瞬态性能
不确定非线性系统
convergence
iterative learning control
transient performance
uncertain nonlinear systems