Automaton-Guided Control Synthesis for Signal Temporal Logic Specifications

TL;DR

This paper introduces an automaton-guided control synthesis framework for continuous dynamical systems with STL specifications, enabling efficient, correct, and probabilistically complete controller design with significant speed improvements.

Contribution

We develop a novel automaton-based approach for control synthesis from STL specifications, applicable to nonlinear systems, with proven correctness and probabilistic completeness.

Findings

Order of magnitude speedup over existing methods

Successful synthesis for nonlinear dynamics with polynomial predicates

Validated on multiple case studies demonstrating efficiency

Abstract

This paper presents an algorithmic framework for control synthesis of continuous dynamical systems subject to signal temporal logic (STL) specifications. We propose a novel algorithm to obtain a time-partitioned finite automaton from an STL specification, and introduce a multi-layered framework that utilizes this automaton to guide a sampling-based search tree both spatially and temporally. Our approach is able to synthesize a controller for nonlinear dynamics and polynomial predicate functions. We prove the correctness and probabilistic completeness of our algorithm, and illustrate the efficiency and efficacy of our framework on several case studies. Our results show an order of magnitude speedup over the state of the art.