本文選題：非線性Volterra濾波器 + 車輪轉(zhuǎn)速信號(hào)��； 參考：《蘭州大學(xué)學(xué)報(bào)(自然科學(xué)版)》2017年02期

【摘要】：為保證機(jī)車黏著控制品質(zhì),提出車輪轉(zhuǎn)速信號(hào)所含混合噪聲(高斯噪聲和沖擊噪聲)的非線性Volterra濾波方法,并結(jié)合混沌優(yōu)化策略及動(dòng)態(tài)隨機(jī)局部搜索算子,提出動(dòng)態(tài)隨機(jī)局部搜索生物地理優(yōu)化算法對(duì)Volterra濾波器模型參數(shù)進(jìn)行優(yōu)化求解.利用Volterra濾波器的結(jié)構(gòu)優(yōu)勢(shì)(具有預(yù)測(cè)性能、兼具線性和非線性項(xiàng)),既能濾除混合噪聲又可滿足黏著控制的實(shí)時(shí)性要求.仿真實(shí)驗(yàn)結(jié)果表明,經(jīng)優(yōu)化求解的非線性Volterra濾波器實(shí)現(xiàn)了對(duì)車輪轉(zhuǎn)速信號(hào)所含混合噪聲的有效濾除.
[Abstract]:In order to ensure the quality of locomotive adhesion control, a nonlinear Volterra filtering method for mixed noise (Gao Si noise and shock noise) in wheel speed signal is proposed, which combines chaos optimization strategy and dynamic random local search operator. A dynamic random local search biogeographic optimization algorithm is proposed to optimize the parameters of Volterra filter model. Taking advantage of the structural advantages of Volterra filters (predictive performance, both linear and nonlinear terms), the mixed noise can be filtered and the real-time requirements of adhesive control can be satisfied. The simulation results show that the optimized nonlinear Volterra filter can effectively remove the mixed noise from the wheel speed signal.
【作者單位】： 蘭州交通大學(xué)機(jī)電工程學(xué)院;
【基金】：國家自然科學(xué)基金項(xiàng)目(51665027,11462011)
【分類號(hào)】：TN713;U260
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本文編號(hào)：1945307