严格反馈互联系统分散式backstepping自适应迭代学习控制

基于Lyapunov分析方法,针对具有严格反馈形式的非线性互联系统,本文设计了一种分散式backstepping自适应迭代学习控制器.子系统之间的互联项为所有子系统输出项线性有界,为每个子系统设计的控制器仅采用该子系统的信息,不需要子系统之间相互传递信息.在控制器中,引入在时间轴和迭代轴上同时更新的自适应参数,以补偿子系统之间的互联项影响.通过采用本文给出的控制器,可使得每个子系统的输出跟踪相应的参考模型输出,仿真结果验证了本文算法的有效性.

Decentralized backstepping adaptive iterative learning control for a class of interconnected nonlinear systems with strict feedback form

Based on the Lyapunov synthesis approach, a decentralized backstepping adaptive iterative learning control scheme is proposed for a class of interconnected nonlinear systems of strict feedback form. The interconnections among subsystems are considered to be bounded by first order polynomials of subsystem outputs. The proposed controller of each subsystem depends only on local state variables without any information exchange with other subsystems. The adaptive parameters are updated along both iteration axis and time one to counter the effects of the interconnections. It is shown that by using the proposed decentralized controller, the outputs of the subsystems can track the desired reference outputs iteratively. Our simulation results show that the output tracking error of each subsystem converges along the iterative axis.