保证瞬态性能的迭代学习控制

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.

Iterative learning control with guaranteed transient performance

For a class of uncertain nonlinear time-varying systems, we present an iterative learning control scheme guaranteeing transient performance bounds. By introducing an error transformation, we convert the problem of guaranteeing transient performance of the tracking error to that of ensuring boundedness of the transformed error. Applying Lyapunov synthesis, we carry out the control design for handling both parametric and nonparametric uncertainties of system dynamics. It is shown that, with the use of fully-saturated learning mechanisms, the system output can completely track the desired trajectory over the entire pre-specified time interval as the number of iteration increases, and the tracking error is confined within the transient performance bounds for each iteration cycle, while the boundedness and the uniform convergence of the transformed error are guaranteed. Simulation results are presented to demonstrate the effectiveness of this learning control method.