Delay-Range-DependentMethod for Iterative LearningFault-Tolerant Guaranteed Cost Control for Batch Processes.

This paper addresses the problem of delay-range-dependentiterativelearning reliable guaranteed cost control of a class of batch processeswith uncertainties, state delay and actuator failures, where the maincontribution is in the relevant concept of H∞iterative learning fault-tolerant guaranteed costcontrol based on an equivalent two-dimensional system descriptionof these processes. The H∞iterativelearning reliable guaranteed cost controller (ILRGCC) is formulatedto include a robust extended feedback control for ensuring the performancesover time and an iterative learning control (ILC) for improving thetracking performance from cycle to cycle, such that it can not onlyguarantee the closed-loop convergence along both the time and thecycle directions but also satisfy both the H∞performance index and a cost function preserving upperbounds for all admissible uncertainties and any actuator failures.To achieve the least guaranteed cost for the closed-loop system, aconvex optimization problem with linear matrix inequality (LMI) constraintsis formulated for the design of the optimal guaranteed cost controllersuch that the delay-range-dependent existing condition of the proposedILRGCC design can also be given by LMIs, where the lower and upperdelay bounds only change along time tdirection.An illustrative example of applications to the nozzle packing pressurecontrol in injection molding has been developed to demonstrate theeffectiveness and merits of the proposed method. [ABSTRACT FROM AUTHOR]