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.
关键词
预测函数控制/非线性控制/随机NARMAX模型/可变基函数/直接极小化指标函数优化算法
Key words
Predictive function control/nonlinear control/random NARMAX model,variable basis function/optimization algorithm for direct minimization of index function
维普
万方数据