Detection,isolation and handling of actuator faults in distributed model predictive control systems

In this work, we focus on monitoring and reconfiguration of distributed model predictive control systems applied to general nonlinear processes in the presence of control actuator faults. Specifically, we consider nonlinear process systems controlled with a distributed control scheme in which two Lyapunov-based model predictive controllers manipulate two different sets of control inputs and coordinate their actions to achieve the desired closed-loop stability and performance specifications. To deal with control actuator faults which may reduce the ability of the distributed control system to stabilize the process, a model-based fault detection and isolation and fault-tolerant control system which detects and isolates actuator faults and determines how to reconfigure the distributed control system to handle the actuator faults while maintaining closed-loop stability is designed. A detailed mathematical analysis is carried out to determine precise conditions for the stabilizability of the fault detection and isolation and fault-tolerant control system. A chemical process example, consisting of two continuous stirred tank reactors and a flash tank separator with a recycle stream and involving stabilization of an unstable steady-state, is used to demonstrate the approach.