非线性系统开闭环PD型迭代学习控制的鲁棒性

Robustness of nonlinear systems with open-closed-loop PD-type iterative learning control

利用开闭环PD型迭代学习控制算法,对一类具有不确定性或扰动的重复非线性时变系统的鲁棒性进行研究,给出了该系统在开闭环PD型迭代学习控制律控制下的鲁棒条件,并证明了该受扰系统在干扰有界的情况下跟踪误差的一致有界收敛性,当所有干扰渐近消失时,系统输出渐近跟踪给定的期望轨迹。数字仿真表明了结论的有效性。

With the open-closed-loop PD iterative learning control algorithm, the robustness of a class of repeated nonlinear time-varying systems containing uncertainties or disturbances is studied. The conditions guaranteeing the robustness of the closed-loop systems are proposed. It is proved that the tracking error of the controlled system is uniformly bounded, and the output of the system can track the desired trajectory asymptotically if all the disturbances are gradually disappeared. A numerical simulation is given to illustrate the efficiency of the results.