4.6 Article

Optimal Control of Colored Timed Petri Nets Under Generalized Mutual Exclusion Temporal Constraints

Journal

IEEE ACCESS
Volume 10, Issue -, Pages 110849-110861

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3216043

Keywords

Petri nets; Integer linear programming; Manufacturing systems; Optimal control; Safety; Discrete-event systems; Job shop scheduling; Petri nets; coloured timed Petri nets; temporal logic; generalized mutual exclusion constraints; integer linear programming

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This study presents a method to solve the optimal control problem in a coloured timed Petri net using coloured generalized mutual exclusion temporal constraints described by signal temporal logic formula, and solving the problem by transforming it into an integer linear programming problem. The effectiveness of the proposed approach is demonstrated through a simulation of an optimal control problem in a manufacturing system.
A coloured Petri net (CPN) is widely used to model discrete event systems due to its compact representation of the system by colour sets associated with places, transitions and I/O arcs. For real-world systems such as manufacturing systems, transportation systems, and communication protocols, a coloured timed Petri net (CTPN) is proposed to model timed behaviours. To control a discrete event system with a desired control specification, it is important to describe the control specification formally. For the CPN, a class of specification called coloured generalized mutual exclusion constraints (cGMEC) is utilized to specify the behaviours. However, cGMEC can only represent safety constraints and not temporal constraints. Therefore, in this paper, we propose a novel temporal logic based constraint called a coloured generalized mutual exclusion temporal constraint (cGMETC). The cGMETC is described by a signal temporal logic (STL) formula where each atomic predicate represents a cGMEC. We propose a method for optimal control of the CTPN under a given cGMETC. In particular, we formulate an optimal control problem and solve the problem by transforming it into an integer linear programming problem. Through a simulation of an optimal control problem of a manufacturing system, we demonstrate the effectiveness of the proposed approach.

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