Abstract
For automated manufacturing systems (AMSs), deadlock resolution in terms of Petri nets remains an attractive topic to which many approaches are dedicated. However, few of them can quantitatively optimize certain indices during their supervisor synthesis process. This causes unnecessary control limitations and often leads to high implementation cost. In the framework of Petri nets, this paper proposes a method to synthesize a cost-effective supervisor with the aid of a set of mathematical programming formulations. Along the same vein, we also show some results by investigating timed Petri nets, which can be utilized to make a good tradeoff between implementation cost and system cycle time. Examples are used to validate the effectiveness of our result.
Note to Practitioners-For a supervisory controller in any AMS, two indispensable elements are observation and control units which can be realized by sensors and actuators, respectively. In terms of Petri nets, they correspond to the in-going and out-going arcs of control places. A controlled system requiring excessive sensors and actuators poses serious cost and reliability concerns. This paper presents a method to derive the supervisors with minimum cost. On the basis of this, it extends the result to timed Petri nets in order to facilitate the comprehensive evaluation of the control cost and system efficiency. The method is formulated as mathematical models whose effectiveness is evaluated via numerical experiments.