Maximally Permissive Robustness Analysis of Automated Manufacturing Systems With Multiple Unreliable Resources

Abstract

For real-world automated manufacturing systems (AMSs), the failures of multiple unreliable resources are very common. Maximal permissiveness is a key aspect for evaluating the performance of robust control strategies of failure-prone AMSs. However, there exist fewer works in the existing literature that can achieve maximally permissive robustness analysis. This may impede the applicability of existing robust control strategies in realistic AMSs. This article tackles the issue in the paradigm of Petri nets (PNs). We present an innovative mechanism to formalize unreliable resource failures by preventing all ingoing transitions of unreliable resource places from firing. Both reachability graph-based and integer linear programming-based methods are proposed to analyze the robustness of AMSs with either single or multiple unreliable resources. Several examples are proposed to illustrate the approach.