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本文针对多变量有约束区域预测控制问题,提出一种基于加权的区域预测控制算法。该方法首先利用实际输出与预测输出之间的偏差对模型预测输出进行修正并对约束区域进行软约束处理,在此基础上对约束区域进行分段处理,最后提出基于加权的区域预测控制方法。该方法根据预测输出与给定区域之间的偏离值设定误差加权矩阵,如果预测输出超出给定区域,则重新计算控制变量的变化量,进而构成一种基于加权的区域预测控制算法。将本文方法与传统方法进行对比仿真研究。仿真结果表明:该方法能使违反区域的被控变量能快速返回给定区域,并能保证系统的稳定性,很好的协调了控制的快速性与保持系统稳定性之间的矛盾。
In this paper, aiming at the problem of multivariable constrained region predictive control, a weight-based region predictive control algorithm is proposed. Firstly, the method predicts the output of the model by using the deviation between the actual output and the predicted output and performs soft constraint on the constrained region. Based on this, the constrained region is segmented. Finally, a weighted region-based predictive control method is proposed. The method sets the error weighting matrix according to the deviation value between the predicted output and the given area. If the predicted output exceeds the given area, the variation of the control variable is recalculated, and then a weighted prediction control algorithm is constructed. This paper compares the method with the traditional method. The simulation results show that the proposed method can make the controlled variables that violate the region quickly return to a given area, and can guarantee the stability of the system, and well coordinate the contradiction between the rapidity of control and the stability of the system.