不确定时滞系统鲁棒迭代学习控制器设计

Design of a Robust Iterative Learning Controller for Uncertain Time-delay Systems

针对一类具有时变的不确定性时滞系统提出鲁棒迭代学习控制器设计方法,通过求解Riccati方程方法设计鲁棒迭代学习控制器,并基于Lyapunov理论推导出不确定时滞系统收敛充要条件。该控制器具有阶次低,易于实现等特点,所提出的控制方案保证系统跟踪在有限的迭代步骤内达到较好的控制效果。以机器人为仿真对象的仿真结果表明了该设计方法的有效性和可行性。

A design of robust iterative learning controller is proposed for uncertain time-delay systems. The controller is obtained by resolving Riccati equation. In addition, the sufficient and necessary conditions of convergence are derived by Lyapunov theory. The proposed controller has lower order and can be easily realized. The scheme proposed guarantees that the system tracking obtains satisfactory control effect within finite iterations. Finally, a simulation experiment is carried out on a two-link planar robot, with the results showing that the proposed method is not only feasible, but also effective.