Formal synthesis of analytic controllers for sampled-data systems via genetic programming
Cees Ferdinand Verdier (TU Delft - Team Tamas Keviczky)
M. Mazo Espinosa (TU Delft - Team Tamas Keviczky)
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Abstract
This paper presents an automatic formal controller synthesis method for nonlinear sampled-data systems with safety and reachability specifications. Fundamentally, the presented method is not restricted to polynomial systems and controllers. We consider a periodically switched controllers based on a Control Lyapunov Barrier-like function. The proposed method utilizes genetic programming to synthesize these function in analytic form, as well as the controller modes. Correctness of the controller are subsequently verified by means of a Satisfiability Modulo Theories solver. Effectiveness of the proposed methodology is demonstrated on multiple systems.