Iterative learning control applied to batch processes: An overview |
| |
Affiliation: | 1. School of Chemical Engineering, Georgia Institute of Technology, 311 Ferst Dr. NW, Atlanta, GA 30332-0100, USA;2. Department of Chemical and Biomolecular Engineering, Sogang University, 1-Shinsoodong, Mapogu, Seoul 121-742, Republic of Korea;1. Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, USA;1. Department of Chemical Engineering, Federal University of Rio Grande do Sul, R. Luiz Englert, s/n, 12204, Porto Alegre, RS 90040-040, Brazil |
| |
Abstract: | With the recent emphasis on batch processing by emerging industries like the microelectronics and biotechnology, the interest in batch process control has been renewed. This paper gives an overview of the iterative learning control (ILC) technique, which can be used to improve tracking control performance in batch processes. The fundamental concepts and review of the various ILC algorithms are presented, with a particular focus on a model-based algorithm called Q-ILC and an application involving a rapid thermal processing (RTP) system. The study indicates that one can solve a seemingly very difficult multivariable nonlinear tracking problem with relative ease by intelligently combining the ILC technique with basic process insights and standard system identification techniques. Some related techniques in the literature are brought forth with the hope of unifying them. We aslo suggest some remaining challenges. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|