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Communication Dans Un Congrès Année : 2020

Lazy Safety Controller Synthesis with Multi-Scale Adaptive-Sampling Abstractions of Nonlinear Systems

Elena Ivanova
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Antoine Girard

Résumé

In this paper, we consider the problem of computation of efficient symbolic abstractions for a certain subclass of continuous-time monotone control systems. The new abstraction algorithm utilizes the properties of such systems to build symbolic models with the same number of states but fewer transitions in comparison to the one produced by the standard algorithm. At the same time, the new abstract system is at least as controllable as the standard one. The proposed algorithm is based on the solution of a region-to-region control synthesis problem. This solution is formally obtained using the theory of viscosity solutions of the dynamic programming equation and the theory of differential equations with discontinuous right-hand side. In the new abstraction algorithm the symbolic controls are essentially the feedback controllers which solve this control synthesis problem. The improvement in the number of transitions is achieved by reducing the number of successors for each symbolic control. The approach is illustrated by an example which compares the two abstraction algorithms.
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Dates et versions

hal-02554329 , version 1 (25-04-2020)

Identifiants

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Elena Ivanova, Antoine Girard. Lazy Safety Controller Synthesis with Multi-Scale Adaptive-Sampling Abstractions of Nonlinear Systems. IFAC 2020 - 21st IFAC World Congress, Jul 2020, Berlin, Germany. ⟨10.1016/j.ifacol.2020.12.2348⟩. ⟨hal-02554329⟩
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