Design and implementation fault tolerant model predictive control scheme on a simulated model of a three-tank hybrid system

Significant research has been carried out over the past three decades in the area of fault tolerant control. Most methods available in the chemical engineering literature are capable of detecting, identifying, estimating and accommodating faults for nonlinear processes with continuous states without state dependent and controlled switching. This work is aimed at developing a method for diagnosing and accommodating faults in a nonlinear three-tank hybrid system (autonomous switching of dynamics) using an Ensemble Kalman filter based fault diagnosis scheme. The online accommodation scheme described by Deshpande et al. for nonlinear systems has been extended to nonlinear autonomous hybrid systems using the proposed method. The efficacy of the proposed Fault-tolerant derivative free state estimation based model predictive control scheme is demonstrated by conducting simulation studies on a benchmark three-tank hybrid system.