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Unsupervised robust recursive least-squares algorithm for impulsive noise filtering

Science China(Information Sciences) 2013年第4期56卷 203-212页

作者： CHEN Jie MA Tao CHEN WenJie PENG ZhiHong School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision(Beijing Institute of Technology) Ministry of Education

A robust recursive least-squares(RLS) adaptive filter against impulsive noise is proposed for the situation of an unknown desired *** minimizing a saturable nonlinear constrained unsupervised cost function instead of the conventional least-squares function,a possible impulse-corrupted signal is prevented from entering the filter’s weight updating ***,a multi-step adaptive filter is devised to reconstruct the observed "impulse-free" noisy sequence,and whenever impulsive noise is detected,the impulse contaminated samples are replaced by predictive *** on simulation and experimental results,the proposed unsupervised robust recursive least-square adaptive filter performs as well as conventional RLS filters in "impulse-free" circumstances,and is effective in restricting large disturbances such as impulsive noise when the RLS and the more recent unsupervised adaptive filter fails.

关键词： unsupervised adaptive filtering impulsive noise suppression recursive least-squares algorithm

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Estimating Wheel-road Vertical Load for Nonlinear Vehicle Vibration System Based on Cubature Kalman Filter

Estimating Wheel-road Vertical Load for Nonlinear Vehicle Vi...

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第30届中国控制与决策会议

作者： Yuexin Zhang Lihui Wang Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of education School of Instrument Science and Engineering Southeast University

The vibration of vehicle is most governed by the load generated of the road roughness, which can affect comfort of vehicle and cause fatigue damage of the vehicle suspension. So knowledge of the load is very important for vehicle control systems to enhance vehicle stability and safety. During the process of the estimation, noise affects the identification accuracy, and maybe cause divergence. The cubature Kalman filter（CKF） has good accuracy performance, numerical stability and computational costs. So this paper presented a new methodology based on CKF and a recursive least-squares algorithm for estimating wheel-road vertical load. The state equations and measurement equations were established according to the second order vibration system, and RK4 was employed to discretize the continuous-time equations. The CKF was used to calculate the residual innovation sequences and the residual innovation sequences were used to calculate the vertical load. To verify the effectiveness of the identification method, numerical simulations of the five degrees of freedom vehicle vibration system subjected to white noises and four types of forces were employed. Simulation results validated and proved the feasibility of this approach.

关键词： Vertical load Five degrees of freedom vehicle vibration system Cubature Kalman filter recursive least-squares algorithm Vehicle stability

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