针对用常规自适应滤波器实现噪声抵消,在没有或很少先验概率的情况下,消除噪声效果很差,阻碍了自适应消噪在实际中的应用.为此,将模型预测控制结构引入自适应噪声抵消.基于模型预测控制的自适应噪声抵消方法利用已有误差控制和预测的误差控制对自适应滤波器的权值进行优化,能够很好地克服系统非线性带来的扰动.理论推导和仿真表明:该方法对先验概率的依赖性小,可以实现实时性的噪声消除,具有良好的鲁棒特性.其特点是利用已有误差控制和预测的误差控制对自适应滤波器的权值进行优化,能够很好地克服系统非线性带来的扰动.%With few prior probability, the effect of conventional adaptive filter noise cancellation is poor, which hinders the adaptive noise cancellation for actual application. The model predictive control structure was introduced to adaptive noise cancellation. Adaptive noise canceller based on model predictive control used existing error control and predicting error control to optimize the weights of the adaptive filter, which could overcome the system nonlinear disturbance effectively. Theoretical analysis and simulation results showed that the method was of little dependence on the prior probability and of high robust,which could fulfill a real-time noise cancellation. The method was characterized by the use of existing error control and prediction error control to optimize the weights of the adaptive filter and overcome the nonlinear disturbance.
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