非线性滞后离散系统的学习控制算法

摘要

讨论了滞后非线性离散系统的学习控制问题，由于所给的学习算法及学习控制过程中，没有涉及和用到相应于理想输出yd的理想输入ud及对应于系统的理想状态xd，故对被控对象的动力学信息要求得很少，只是一种定性上的Lipschitz条件.所给出的控制算法不仅收敛，而且也保证了对期望目标在通常意义下的跟踪（而不是像目前有些结果那样，只是跟踪到期望目标的某一个邻域范围内）.而且这些算法还以目前一些通常的算法为特例.%In this paper, we discuss the learning control for nonlinear discrete system with delay. It is not necessary to use the desired input corresponding to the desired output and the desired state corresponding to the system in our learning algorithm and in the process of learning control. Therefore, our method needs less dynamics information of the controlled object than previous ones and only the qualitative Lipschitz condition is required. Not only is the learning algorithm convergent, but also it can track the desired target in common sense (not tracking the desired target only in a neighborhood as the existing ones). Our algorithim includes some existing ones as its special cares.