Predictive functional control with reduced-order observer based PSO for pneumatic positioning control

The employment of Particle Swarm Optimization (PSO) algorithm in determining the best value of parameter alpha (Psi) for Predictive Functional Control (PFC) used in pneumatic system was proposed in this study. A reduced-order observer was used together with PFC to estimate the internal states of pneumatic system. The performance of Predictive Functional Control with Reduced-order Observer (PFCRO) with and without employment of PSO were compared. The validation was done in simulation and experiment using MATLAB/Simulink. The results revealed that PFCRO using PSO gave better response in controlling the pneumatic positioning system compared to PFCRO without using PSO.