文章基本信息

标题：Stochastic Model Predictive Control with Integrated Experiment Design for Nonlinear Systems
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作者：Vinay A. Bavdekar ; Ali Mesbah
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：7
页码：49-54
DOI：10.1016/j.ifacol.2016.07.215
语种：English
出版社：Elsevier
摘要：The performance of predictive control strategies often degrades over time due to growing plant-model mismatch. Closed-loop performance restoration typically requires some form of model maintenance to reduce model uncertainty. This paper presents a stochastic predictive control approach with integrated experiment design for nonlinear systems with probabilistic modeling uncertainties. The integration of predictive control with experiment design enables enhancing the information content of closed-loop data for online model adaption. The presented approach considers control-oriented experiment design to ensure adequate model adaptation (in probability) in terms of an admissible control performance level. The stochastic optimal control approach is demonstrated on a continuous bioreactor case study.
关键词：Dual predictive controlStochastic optimal controlControl-oriented model adaptation