A Constrained PSO Based Model Predictive Control for Mobile Robot System with Sensor Faults

This paper presents a fault-tolerant predictive control based on Particle Swarm Optimization, subject to sensors faults and constraints for a mobile robot. To enhancing trajectory-tracking accuracy, a PSO algorithm is proposed for the computation of best candidate predictive controls, based on minimizing a constrained objective criterion. Then, an update of the predictive controller parameters is defined for accurate position of mobile robot. In order to maintain the desired performances against sensor faults, an evaluation function in a PSO algorithm have been established, taking into account constraints and stability conditions in the reformulation of the new augmented system using a state observer. Simulation results prove the ability of the proposed strategy applying to a mobile robot for the trajectory-tracking.