Batch Process Control from Practice to 2D Model Predictive Control
Owing to the natures of batch processes, such as high nonlinearity, time-varying, and limited batch time duration, their control remains as a challenge to modern industries. This paper takes a typical batch process, injection molding, as an example to present a set of control schemes for batch processes. Advanced control algorithms such as adaptive control and model predictive control have been adopted to deal with the inherent process nonlinear and time-varying characteristics. These control algorithms are all focused on single cycle control performance. A multi-cycle two-dimensional model predictive learning control has been developed for batch processes control to take advantages of batch process repeatability. In this presentation, besides showing the control results/methods, the authors wish to illustrate the development evolution with their understanding of the natures of batch processes in general, injection molding in particular.
Batch Process Injection Molding 2D Model Predictive Control Iterative Learning
Ke Yao Yi Yang Furong Gao
Department of Chemical and Biomolecular Engineering, The Hong Kong University of Science & Technology, Hong Kong
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
1-7
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）