文章基本信息

标题：Risk-Sensitive Model Predictive Control with Gaussian Process Models *
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作者：Xiaoke Yang ; Jan Maciejowski
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：28
页码：374-379
DOI：10.1016/j.ifacol.2015.12.156
语种：English
出版社：Elsevier
摘要：AbstractThis paper proposes the use of risk-sensitive costs in a model predictive controller (MPC) with Gaussian process (GP) models, for more effective online learning and control. Being a probabilistic model, a GP incorporates the uncertainty information due to imperfect knowledge of the system. The MPC then utilises this uncertainty information in a risk-sensitive, especially risk-seeking fashion, to balance the exploration of the unknown characteristics and the exploitative control actions simultaneously. Comparison of MPCs with the risk-seeking cost and the risk-neutral cost, i.e. the standard quadratic cost, on the swing-up control of a cart-pendulum system demonstrates that the risk-seeking cost exhibits an effective exploratory behaviour which leads to a better learning of the unknown system and in turn gives improved control performance.
关键词：Keywordsrisk-sensitive controlmodel predictive controlGaussian process modeladaptive controllearning control systems