{"title":"A Stochastic Approach to Maximal Output Admissible Sets and Reference Governors","authors":"Joycer Osorio, H. Ossareh","doi":"10.1109/CCTA.2018.8511439","DOIUrl":null,"url":null,"abstract":"This paper presents a stochastic approach to Reference Governors (RG) and Maximal Output Admissible Sets (MAS) using chance constraints. In order to construct a stochastic robustly invariant MAS (SR-MAS), we extend the earlier ideas in the literature to Lyapunov stable systems with output constraints. Formal proofs for important properties such as positive invariance and finite determinism of SR-MAS are provided. It is shown that the SR-MAS is less conservative than the deterministic approach. An algorithm is provided to compute the SR-MAS in finite time. Finally, we present a stochastic RG formulation, which leverages the SR-MAS. The main results are illustrated with a numerical simulation of a mass-spring-damper model with constraints imposed over the control signal and output.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"233 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Conference on Control Technology and Applications (CCTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCTA.2018.8511439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
This paper presents a stochastic approach to Reference Governors (RG) and Maximal Output Admissible Sets (MAS) using chance constraints. In order to construct a stochastic robustly invariant MAS (SR-MAS), we extend the earlier ideas in the literature to Lyapunov stable systems with output constraints. Formal proofs for important properties such as positive invariance and finite determinism of SR-MAS are provided. It is shown that the SR-MAS is less conservative than the deterministic approach. An algorithm is provided to compute the SR-MAS in finite time. Finally, we present a stochastic RG formulation, which leverages the SR-MAS. The main results are illustrated with a numerical simulation of a mass-spring-damper model with constraints imposed over the control signal and output.