Constraint-Based Approach to Hybrid Dynamical Systems with Uncertainty

ID
TR-2004-05
Authors
Robert St-Aubin and Alan K. Mackworth
Publishing date
April 01, 2004
Length
41 pages
Abstract
Due to the recent technological advances, real-time hybrid dynamical systems are becoming ubiquitous. Most of these systems behave unpredictably, and thus, exhibit uncertainty. Hence, a formal framework to model systems with unpredictable behaviours is needed. We develop Probabilistic Constraint Nets (PCN), a new framework that can handle a wide range of uncertainty, whether it be probabilistic, stochastic or non-deterministic. In PCN, we view probabilistic dynamical systems as online constraint-solvers for dynamic probabilistic constraints and requirements specification as global behavioural constraints on the systems. We demonstrate the power of PCN by applying it to a fully hybrid model of an elevator system which encompasses several different types of uncertainty. We present verification rules, which have been fully implemented, to perform automatic behavioural constraint verification.