01441452

j

01441452 Lee, Jay H. Lee, Kwang S. Kim, Won C. Model-based iterative learning control with a quadratic criterion for time-varying linear systems. Automatica 36, No.5, 641-657 (2000). 2000 Elsevier Science Ltd. (Pergamon), Oxford EN predictive control iterative learning control error transition model optimal control tracking robustness sensitivity

doi:10.1016/S0005-1098(99)00194-6

New model-based Iterative Learning Control (ILC) algorithms for time-varying constrained batch chemical processes with disturbances and noises are presented. A sophisticated error transition model between two adjacent batches is introduced. Based on this model, one-batch-ahead optimal control algorithms are derived for unconstrained and constrained cases. In addition, a robust ILC algorithm which minimizes the worst-case tracking error for the next batch is proposed. For each algorithm, relevant basic properties such as the convergence, robustness, and noise sensitivity are investigated. Several examples are selected to demonstrate the advantages of the proposed ILC algorithms. Ingmar Randvee (Tallinn)