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Title: On Abstraction-Based Controller Design With Output Feedback
We consider abstraction-based design of output-feedback controllers for dynamical systemswith a finite set of inputs and outputs against specifications in linear-time temporal logic. The usual procedure for abstraction-based controller design (ABCD) first constructs a finite-state abstraction of the underlying dynamical system, and second, uses reactive synthesis techniques to compute an abstract state-feedback controller on the abstraction. In this context, our contribution is two-fold: (I) we define a suitable relation between the original systemand its abstractionwhich characterizes the soundness and completeness conditions for an abstract state-feedback controller to be refined to a concrete output-feedback controller for the original system, and (II) we provide an algorithm to compute a sound finite-state abstraction fulfilling this relation. Our relation generalizes feedback-refinement relations fromABCD with state-feedback. Our algorithm for constructing sound finitestate abstractions is inspired by the simultaneous reachability and bisimulation minimization algorithm of Lee and Yannakakis. We lift their idea to the computation of an observation-equivalent system and show how sound abstractions can be obtained by stopping this algorithm at any point. Additionally, our new algorithm produces a realization of the topological closure of the input/output behavior of the original system if it is finite state realizable.
Authors:
; ;
Award ID(s):
1553873
Publication Date:
NSF-PAR ID:
10211270
Journal Name:
Proc. Hybrid Systems Computation and Control (HSCC) 2020.
Sponsoring Org:
National Science Foundation
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