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Variational Bayesian based cubature smooth variable structure filter(PDF)


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Variational Bayesian based cubature smooth variable structure filter
Zhang LeiGuo JianQian ChenChen Qingwei
School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China
variational Bayesian smooth variable structure filter nonlinear state estimation cubature transform
A new cubature smooth variable structure filter algorithm is proposed to decrease the effect of modelling error and unknown measurement noise characteristic on nonlinear state estimation. The nonlinear cubature transform rule is combined to avoid the linearization error. Through the sliding mode variable structure idea,the optimal smoothing boundary layer is calculated to restrict the modelling error. The variational Bayesian is used to estimate the real-time measurement noise characteristic in the dynamic system,and the threshold value of smoothing boundary layer is optimized. The simulation results demonstrate that compared with the traditional nonlinear filter algorithm,the proposed algorithm improves the accuracy by 28.5%,and shows a better filter performance.


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Last Update: 2019-06-30