Model-based diagnosis and control reconfiguration for discrete event systems: an integrated approach

We describe an approach to automate the dynamic computation of optimal control/reconfiguration actions that can achieve pre-specified control objectives. This approach, based on model-based diagnostic representations and algorithms, integrates diagnostics and control reconfiguration for discrete event systems using a single modeling mechanism and suite of algorithms. When the system functionality degrades (i.e., failures occur in the systems), the diagnostic algorithm will isolate the most-likely failures, and then the control mechanism will generate the least-cost actions that attempt to recover from the failure and maintain the control objectives. Results about the quality of the control actions generated and the complexity of computing these actions are also presented. We illustrate our approach using a simple wireless sensor network.