A performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control

Abstract

This paper presents a performance optimization algorithm for controller reconfiguration in fault tol-erant distributed model predictive control for large-scale systems. After the fault has been detectedand diagnosed, several controller reconfigurations are proposed as candidate corrective actions for faultcompensation. The solution of a set of constrained optimization problems with different actuator andsetpoint reconfigurations is derived by means of an original approach, exploiting the information onthe active constraints in the non-faulty subsystems. Thus, the global optimization problem is split intotwo optimization subproblems, which enable the online computational burden to be greatly reduced.Subsequently, the performances of different candidate controller reconfigurations are compared, andthe better performing one is selected and then implemented to compensate the fault effects. Efficacyof the proposed approach has been shown by applying it to the benzene alkylation process, which is abenchmark process in distributed model predictive control.