Research on networked predictive functional controller based on Particle Swarm Optimization

A significant attention has been paid to networked control systems (NCS) during the last few years, but few researches take the uncertainty of the controlled plant into account. This paper investigate the robustness of networked control systems with in model parameter perturbation and external disturbance. For robustness of networked control systems with uncertainty, an improved networked predictive functional controller based on Particle Swarm Optimization (PSO) algorithm is proposed. PSO algorithm is used to optimize the control input value, because the efficiency is higher and the implementation is strong. The algorithm is based on the PSO to obtain the optimal networked predictive functional controller (NPFC) control value to meet the time delay, so as to guarantee the real-time performance and robustness of the control system. The simulation results about DC motor illustrate that the proposed scheme is effective.