Repetitive process based indirect-type iterative learning control for batch processes with model uncertainty and input delay
JOURNAL OF PROCESS CONTROL(2023)
摘要
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-infinity 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.
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关键词
Batch process,Iterative learning control,Input-delay,Repetitive process,Robust H-infinity control,Linear matrix inequality
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