Event-Driven Model Predictive Control of Timed Hybrid Petri Nets

Hybrid Petri nets represent a powerful modeling formalism that offers the possibility of integrating in a natural way continuous and discrete dynamics in a single net model. Usual control approaches for hybrid nets can be divided into discrete-time and continuous-time approaches. Continuous-time approaches are usually more precise but can be computationally prohibitive. Discrete-time approaches are less complex but can entail mode-mismatch errors due to fixed time discretization. This work proposes an optimization-based event-driven control approach that applies on continuous time models and where the control actions change when discrete events occur. Such an approach is computationally feasible for systems of interest in practice and avoids mode-mismatch errors. In order to handle modelling errors and exogenous disturbances, the proposed approach is implemented in a closed-loop strategy based on event-driven model predictive control.