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Title: Duality-Based Nested Controller Synthesis from STL Specifications for Stochastic Linear Systems
We propose an automatic synthesis technique to generate provably correct controllers of stochastic linear dynamical systems for Signal Temporal Logic (STL) specifications. While formal synthesis problems can be directly formulated as exists-forall constraints, the quantifier alternation restricts the scalability of such an approach. We use the duality between a system and its proof of correctness to partially alleviate this challenge. We decompose the controller synthesis into two subproblems, each addressing orthogonal concerns - stabilization with respect to the noise, and meeting the STL specification. The overall controller is a nested controller comprising of the feedback controller for noise cancellation and an open loop controller for STL satisfaction. The correct-by-construction compositional synthesis of this nested controller relies on using the guarantees of the feedback controller instead of the controller itself. We use a linear feedback controller as the stabilizing controller for linear systems with bounded additive noise and over-approximate its ellipsoid stability guarantee with a polytope. We then use this over-approximation to formulate a mixed-integer linear programming (MILP) problem to synthesize an open-loop controller that satisfies STL specifications.
Authors:
; ; ;
Award ID(s):
1750009 1740079
Publication Date:
NSF-PAR ID:
10075839
Journal Name:
16th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2018
Page Range or eLocation-ID:
235-251
Sponsoring Org:
National Science Foundation
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