含输入死区系统的滤波误差初始修正迭代学习控制
Filtering-error rectified iterative learning control for systems with input dead-zone

针对一类输入环节含死区非线性特性且误差初值非零的非参数不确定系统, 提出滤波误差初始修正学习 控制方案, 分别解决死区斜率下限可知与未知两种情形下的轨迹跟踪问题. 给出了两种修正滤波误差信号构造方 法, 并根据Lyapunov综合方法设计学习控制器, 采用鲁棒学习策略处理非参数不确定性和死区非线性特性. 经过足 够多次迭代后, 实现滤波误差在预设的作业区间也收敛于零. 文中所提出的控制方案, 具有构造简单与实施方便的 特点, 仿真结果表明了本文所提控制方法的有效性.
This paper presents the filtering-error rectified adaptive iterative learning control algorithms to tackle the trajectory??tracking problem for a class of nonparametric uncertain systems with unknown input dead-zone, in the presence of arbitrary initial states. To overcome the arbitrary initial states, two construction programs of the rectified filtering-error are proposed. Two iterative learning controllers are designed by applying Lyapunov synthesis, suitable to the case that the lower bound of the dead-zone’s slope is known and the case that it is unknown respectively, dealing with the nonparametric uncertainties and the unknown dead-zone nonlinearity according to the robust learning strategy. As iteration increases, the filtering error converges to zero on the specified interval. The rectified filtering-error signal can be simply constructed, and the proposed learning control scheme, whose effectiveness is demonstrated in the presented numerical results, is easy for implementation.