Abstract
In recent decades, deadlock control for automated manufacturing systems has been an active area. Most researchers have assumed that allocated resources, such as sensors, actuators, and controllers never fail. However, this case is not prevalent in practice due to the unexpected failure of resources. Thus, the objective of robust control is presented in this article. Several methods have been developed along this direction, such as methods that combine neighborhood constraints and the modified Banker's algorithm, as well as methods based on critical places. To explore their effectiveness and performance, we not only conduct a comparison investigation but also develop new theoretical results. According to the experimental results, critical place-based approaches are simpler, more efficient, and more comprehensive than the Banker's algorithm-based approaches in response to resource failures. This article is motivated by the control of production Petri nets; however, the results are also applicable to other more complex systems.