Automated Formal Synthesis of Digital Controllers for State-Space Physical Plants

Research output: Contribution to journalArticle

  • External authors:
  • Alessandro Abate
  • Iury Bessa
  • Dario Cattaruzza
  • Cristina David
  • Pascal Kesseli
  • Daniel Kroening
  • Elizabeth Polgreen


We present a sound and automated approach to synthesize safe digital feedback controllers for physical plants represented as linear, time-invariant models. Models are given as dynamical equations with inputs, evolving over a continuous state space and accounting for errors due to the digitization of signals by the controller. Our counterexample guided inductive synthesis (CEGIS) approach has two phases: We synthesize a static feedback controller that stabilizes the system but that may not be safe for all initial conditions. Safety is then verified either via BMC or abstract acceleration; if the verification step fails, a counterexample is provided to the synthesis engine and the process iterates until a safe controller is obtained. We demonstrate the practical value of this approach by automatically synthesizing safe controllers for intricate physical plant models from the digital control literature.

Bibliographical metadata

Original languageEnglish
JournalLecture Notes in Computer Science
Early online date13 Jul 2017
Publication statusPublished - 2017