基于在线子空间辨识的自适应预测控制

Adaptive Predictive Control Based on On-line Subspace Identification

针对实际工业工程中存在非线性、时变的特点,提出一种基于子空间辨识的自适应预测控制方法。利用滚动窗口在线更新R阵,得到新的预测模型参数矩阵,通过比较更新前和更新后的预测误差来决定是否更新预测模型。将此控制方法应用于2-CSTR过程控制的仿真试验,通过与自适应模糊控制、PID控制器的比较,说明了该方法的优越性。

In order to deal with nonlinear and time-varying characteristics in the practical industrial processes,an adaptive predictive control method based on subspace identification was proposed.Through on-line updating the R matrix with receding window,the new prediction model parameter matrixes were obtained.By comparing the prediction error before and after updating,it considers whether or not to update the prediction model.This control method was applied to the process control simulation on a 2-CSTR.Through comparisons of performance with an adaptive fuzzy control scheme and PID controller,the superiority of the proposed control method is illustrated.