{"title":"Improving validated computation of Viability Kernels","authors":"Benjamin Martin, Olivier Mullier","doi":"10.1145/3178126.3178141","DOIUrl":null,"url":null,"abstract":"The study of viability kernels can be of critical importance for the verification of control systems. A viability kernel over a set of safe states is the set of initial states for which the trajectory can be controlled so as to stay within the safe set for an indefinite amount of time. This paper investigates improvements of the rigorous method from Monnet et al. [19, 20]. This method computes an inner-approximation of the viability kernel of a continuous time control system using methods based on interval analysis. It consists of two phases: first an initial inner-approximation of the viability kernel is computed via Lyapunov-like functions; second the initial inner-approximation is improved by finding other states that can reach the inner-approximation, without exiting the safe set, using validated numerical integration. Among the improvements, we discuss an approach inspired by an interval method using barrier functions for computing a good initial inner-approximation of the viability kernel, easing the improvement phase.","PeriodicalId":131076,"journal":{"name":"Proceedings of the 21st International Conference on Hybrid Systems: Computation and Control (part of CPS Week)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 21st International Conference on Hybrid Systems: Computation and Control (part of CPS Week)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3178126.3178141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The study of viability kernels can be of critical importance for the verification of control systems. A viability kernel over a set of safe states is the set of initial states for which the trajectory can be controlled so as to stay within the safe set for an indefinite amount of time. This paper investigates improvements of the rigorous method from Monnet et al. [19, 20]. This method computes an inner-approximation of the viability kernel of a continuous time control system using methods based on interval analysis. It consists of two phases: first an initial inner-approximation of the viability kernel is computed via Lyapunov-like functions; second the initial inner-approximation is improved by finding other states that can reach the inner-approximation, without exiting the safe set, using validated numerical integration. Among the improvements, we discuss an approach inspired by an interval method using barrier functions for computing a good initial inner-approximation of the viability kernel, easing the improvement phase.