Variable abstraction and approximations in supervisory control synthesis

This paper proposes a method to simplify Extended Finite-state Automata (EFA) in such a way the least restrictive controllable supervisor is preserved. The method is based on variable abstraction, which involves the identification and removal of irrelevant variables from a model. Variable abstraction preserves controllability, and the paper shows how approximations can be used to ascertain least restrictiveness of the synthesis result. The approach has the modelling benefits of Extended Finite-state Automata, leads to optimal control solutions, and reduces the synthesis cost. An example of a manufacturing system illustrates the contributions

Constructing (Bi)Similar Finite State Abstractions using Asynchronous ll-Complete Approximations

This paper constructs a finite state abstraction of a possibly continuous-time and infinite state model in two steps. First, a finite external signal space is added, generating a so called $\Phi$-dynamical system. Secondly, the strongest asynchronous $l$-complete approximation of the external dynamics is constructed. As our main results, we show that (i) the abstraction simulates the original system, and (ii) bisimilarity between the original system and its abstraction holds, if and only if the original system is $l$-complete and its state space satisfies an additional property

Sparsity-Sensitive Finite Abstraction

Abstraction of a continuous-space model into a finite state and input dynamical model is a key step in formal controller synthesis tools. To date, these software tools have been limited to systems of modest size (typically $\leq$ 6 dimensions) because the abstraction procedure suffers from an exponential runtime with respect to the sum of state and input dimensions. We present a simple modification to the abstraction algorithm that dramatically reduces the computation time for systems exhibiting a sparse interconnection structure. This modified procedure recovers the same abstraction as the one computed by a brute force algorithm that disregards the sparsity. Examples highlight speed-ups from existing benchmarks in the literature, synthesis of a safety supervisory controller for a 12-dimensional and abstraction of a 51-dimensional vehicular traffic network