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 faults or external system changes. So even if a fault is diagnosed correctly, the system normally needs to be repaired manually by a human operator. To implement the vision of an autonomous system, besides self-diagnosis 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 fora fault can be modeled explicitly. Unfortunately, such models are hardly available for such systems. To solve this challenge, in this paper, a novel approach for the automated reconfiguration of CPPS is presented. It is based on Satisfiability Modulo Theories and operates on observed system data as well as on information about the system topology. By doing this, the modeling efforts are reduced. To evaluate this new approach, a simulation of such CPPS is used