English

Formal Synthesis of Analytic Controllers for Sampled-Data Systems via Genetic Programming

Systems and Control 2018-12-07 v1 Neural and Evolutionary Computing

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 periodically switched controllers based on a Control Lyapunov Barrier-like functions. The proposed method utilizes genetic programming to synthesize these functions 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.

Keywords

Cite

@article{arxiv.1812.02711,
  title  = {Formal Synthesis of Analytic Controllers for Sampled-Data Systems via Genetic Programming},
  author = {Cees F. Verdier and Manuel Mazo},
  journal= {arXiv preprint arXiv:1812.02711},
  year   = {2018}
}

Comments

The original version of this article has been accepted to CDC 2018. This version contains minor corrections. Supported by NWO Domain TTW under the CADUSY project \#13852

R2 v1 2026-06-23T06:34:35.774Z