Nonlinear Predictive Functional Control Based On Support Vector Machine

Apply predictive function control into nonlinear system and propose a nonlinear control algorithm with supported vector machine. Nonlinear object is identified by supported vector machine of linear kernel function so that predictive model and base function response are obtained. Then explicit mathematic expression of control law for nonlinear model is optimized to create following mechanism of predictive function control and control algorithm is given. Simulation results prove that this algorithm can effectively handle nonlinear process. It has less computation parameters and better track and rejecting disturbance performance.