基于递推最小二乘法与模糊自适应扩展卡尔曼滤波相结合的车辆状态估计OA北大核心CSCDCSTPCD
Vehicle State Estimation Based on Combined RLS and FAEKF
针对汽车状态估计中模型参数的变化和观测噪声的时变特性,提出了递推最小二乘法与模糊自适应扩展卡尔曼滤波相结合的汽车状态估计算法.为实现模型参数与观测噪声的实时更新,建立了基于三自由度非线性车辆动力学模型的算法,首先利用递推最小二乘法对汽车的总质量进行估计,其次建立了模糊控制器对扩展卡尔曼滤波的观测噪声进行实时跟踪.在搭建的CarSim与MATLAB/Sim-ulink联合仿真平台中验证了该算法的有效性,结果表明该算法估计精度高于传统扩展卡尔曼滤波算…查看全部>>
For the problems of observation noise time-varying characteristics and model parameter variations in vehicle state estimation,a new algorithm which consisted of RLS method and FAEKF was proposed.The new algorithm was proposed based on 3-DOF nonlinear vehicle dynamics model in order to realize real time update of model parameters and observation noises.Firstly,the total mass of the vehicle was estimated by RLS.Then,a fuzzy controller was established to track …查看全部>>
汪;魏民祥;赵万忠;张凤娇;严明月
南京航空航天大学能源与动力学院,南京,210016南京航空航天大学能源与动力学院,南京,210016南京航空航天大学能源与动力学院,南京,210016南京航空航天大学能源与动力学院,南京,210016常州工学院机械与车辆工程学院,常州,213002
交通工程
汽车总质量估计状态估计递推最小二乘法模糊自适应扩展卡尔曼滤波
automobile total quality estimationstate estimationrecursive least squares(RLS)fuzzy adaptive extended Kalman filter(FAEKF)
《中国机械工程》 2017 (6)
力与位移耦合控制的新型电动轮汽车差速转向机理研究
750-755,6
国家自然科学基金资助项目(51375007)江苏省自然科学基金资助项目(SBK2015022352)常州市科技计划应用基础研究项目(CJ20159011)
评论