Automated Reconfiguration of Cyber-Physical Production Systems using Satisfiability Modulo Theories

Today, Cyber-Physical Production Systems (CPPS) are controlled by manually written software, therefore the software is not able to adapt to unforeseen events and faults. So even if a fault is diagnosed automatically, the system normally needs to be repaired manually by a human operator. So to implement the vision of an autonomous system, besides self-diagnosis also a self-reconfiguration or self-repair step is needed. Here reconfiguration is the task of restoring valid system behavior after an invalid system behavior occurred. For complex CPPS, finding such a new valid configuration always requires a system model covering all potential new configurations-only for rather simple systems the possible reconfigurations for a fault can be modeled explicitly. Unfortunately, such models are hardly available for complex systems. This paper presents a novel approach for the automated reconfiguration of CPPS to solve this challenge. It is based on the combination of residual-based fault detection and logical calculi to draw causal coherences. The approach operates on observed system data and information about the system topology. By doing this, the modeling efforts are reduced. To evaluate the new approach, a simulation of such CPPS is used.