Source data for: Robust indirect-type iterative learning control design for batch processes with state delay, non-repetitive uncertainties and disturbances

A robust indirect-type iterative learning control scheme is developed for batch processes with state delays, time-varying uncertainties, and disturbances. In contrast to direct-type designs, the new scheme consists of two control loops, each of which can be designed independently. In the inner loop, a control law that is the sum of a generalised extended state observer-based state feedback and proportional plus integral control action acting on an error signal is designed for stability and robustness. The outer loop is designed to update the set-point command for the resulting closed-loop system. Finally, the stability theory for linear repetitive processes ensures robust tracking error convergence for the resulting dynamics in the presence of non-repetitive uncertainties and disturbances. Two numerical examples demonstrate the attributes of the new design.

针对存在状态时滞、时变不确定性与扰动的批次过程，本文提出一种鲁棒间接型迭代学习控制（Indirect-type Iterative Learning Control）方案。与直接型设计方案不同，该新型方案包含两个可独立设计的控制回路。在内环中，本文设计了一种控制律，其由基于广义扩张状态观测器（Generalized Extended State Observer）的状态反馈项与作用于误差信号的比例积分控制项相加构成，以保障系统的稳定性与鲁棒性。外环则用于为所得闭环系统更新设定值指令。最后，依托线性重复过程的稳定性理论，可保证在存在非重复不确定性与扰动的情况下，所得动力学系统的跟踪误差能够实现鲁棒收敛。两组数值算例验证了该新型设计方案的性能特点。