提出一种新型输入加权预测控制器 ,通过对控制输入进行柔化和滤波处理 ,使实际实施的控制量为现时和现时对未来控制时域长度预测控制量的加权平均 ,从而大大减小控制输入的震荡 ,具有较快的响应能力。通过对其结构的分析可知 ,该控制器具有滤波功能 ,能有效抑制模型误差的影响和控制量的震荡 ,克服了文献 [1]需要在线记忆预测控制输入的缺点 ,不仅简化了算法 ,而且大大减少了系统的记忆容量。仿真结果表明了该算法的优异性能 A new type of input weighted prediction controller is presented. By softening and filtering the control input, the actual control amount is the weighted average of the current and the current predicted control amount of the future control time length, which greatly reduces the control input The shock, with faster response. Through the analysis of its structure, it can be seen that this controller has filtering function, which can effectively restrain the influence of model error and control amount of oscillation, and overcome the shortcomings of literature [1] that need online memory predictive control input. It not only simplifies the algorithm but also greatly Reduce the system’s memory capacity. Simulation results show the excellent performance of the algorithm