文章基本信息

标题：Stochastic Iterative Learning Model Predictive Control based on Stochastic Approximation
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作者：ByungJun Park ; Se-Kyu Oh ; Jong Min Lee 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：1
页码：604-609
DOI：10.1016/j.ifacol.2019.06.129
语种：English
出版社：Elsevier
摘要：AbstractIterative learning model predictive control (ILMPC) is an effective control technique for improving the performance of a batch process under model uncertainty and rejecting real-time disturbances. Industrial batch processes often have stochastic disturbance and noise and ILMPC cannot guarantee convergence for such systems. In this work, we propose a novel stochastic ILMPC that combines stochastic approximation with ILMPC algorithm. The proposed algorithm ensures the almost sure convergence property. In comparison with the ILMPC, the proposed control algorithm also shows better performance in terms of the tracking error.
关键词：KeywordsIterative Learning ControlModel Predictive ControlIterative Learning Model Predictive ControlStochastic Approximation