Repetitive process based indirect-type iterative learning control for batch processes with model uncertainty and input delay

• DOI: 10.1016/j.jprocont.2023.103112
• Publication Date: 2023-10-30T18:26:56Z
• Authors: Hongfeng Tao; Junhao Zheng; Junyu Wei; Wojciech Paszke; Eric Rogers; Vladimir Stojanovic
• Keywords: Iterative Learning Control; Batch processing

This paper develops an indirect iterative learning control scheme for batch processes with time-varying uncertainties, input delay, and disturbances. In this paper, a predictor based on a state observer is designed to estimate the future state and to compensate for the input delay. Then a feedback controller based on the estimated state and the set-point error is used to track the specified reference trajectory, where, of the options available, a robust 𝐻∞ controller is designed in the presence of time-varying uncertainties and load disturbances. Then a proportional plus derivative type iterative learning control law is designed. An injection molding process model demonstrates the new method’s effectiveness, and a comparison with a direct-type design is given.<br/>Published<br/>