文章基本信息

标题：Application of Robust Control Barrier Function with Stochastic Disturbance Model for Discrete Time Systems
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作者：Rin Takano ; Hiroyuki Oyama ; Masaki Yamakita 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：31
页码：46-51
DOI：10.1016/j.ifacol.2018.10.009
语种：English
出版社：Elsevier
摘要：AbstractFor engine control systems, there are several constraints to prevent damages of engines due to bad phenomena, eg. knocking. When the dynamics of the systems are modeled as state space representations, the constraints can be represented as state constraints. Therefore, many researchers have studied controllers to achieve good control performances without violating given state constraints. Recently, a new method to solve such constraint control problems has been proposed, which is called CLF-CBF-QP. The control method was proposed first for continuous time systems and was extended to discrete time systems. It can achieve good control performances in the nominal case, however it is impossible to achieve good results in the presence of disturbances. This paper proposes a robust constrained stabilization control using control barrier function and Gaussian process regression for discrete time systems affected by stochastic disturbances, and show an application to the engine control systems.
关键词：KeywordsConstrained SystemControl Barrier FunctionDiscrete time systems