Nonlinear Predictive Function Control of Variable Basis Function with Online Optimization
A nonlinear predictive function control based on practical random NARMAX model was developed so that the basic predictive function control can be applied but not limited to linear system control.The model parameter were estimated with the nonlinear recursive least squares method of overcoming algorithmic ill condi-tion,The original practical random NARMAX model was approximated into a linear time-varying CARMAX model with the method of dynamic cutting horizontal approximating at working point to transform the nonlinear predictive function to the linear predictive function control.The linear optimization algorithm improved compli-cated nonlinear optimization in control input,The weighting coefficient of variable basis function was optimized online with the direct minimization of index function optimization algorithm,and a nonlinear predictive func-tion control with online optimization parameter was proposed.Simulation results showed that the control re-sponse of the system was excellent due to the algorithm's optimized variable basis weighting coefficient and predictive function control.
Predictive function controlnonlinear controlrandom NARMAX model,variable basis functionoptimization algorithm for direct minimization of index function
万方数据
维普
