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为保证机车黏着控制品质,提出车轮转速信号所含混合噪声(高斯噪声和冲击噪声)的非线性Volterra滤波方法,并结合混沌优化策略及动态随机局部搜索算子,提出动态随机局部搜索生物地理优化算法对Volterra滤波器模型参数进行优化求解.利用Volterra滤波器的结构优势(具有预测性能、兼具线性和非线性项),既能滤除混合噪声又可满足黏着控制的实时性要求.仿真实验结果表明,经优化求解的非线性Volterra滤波器实现了对车轮转速信号所含混合噪声的有效滤除.
In order to ensure the quality of locomotive adhesion control, a nonlinear Volterra filtering method of hybrid noise (Gaussian noise and impulsive noise) contained in the wheel speed signal is proposed. Combined with chaos optimization strategy and dynamic random local search operator, a dynamic random local search Algorithm to optimize the parameters of the Volterra filter model.Using the structural advantages of the Volterra filter (with predictive performance, both linear and nonlinear terms), both the hybrid noise and the real-time requirements of the adhesive control can be satisfied.The simulation experiment The results show that the proposed nonlinear Volterra filter can effectively filter mixed noise contained in the wheel speed signal.