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| Vehicle nonlinear state estimation based on strong tracking filter |
1.State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing 400044,China; 2.Ministry of Education Key Laboratory of Manufacture and Test Techniques for Automobile Parts,Chongqing Institute of Technology,Chongqing 400000,China）
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Abstract To solve the problem that some key state parameters in vehicle stability control process are difficult to measure directly,the state optimization estimation algorithm of multi-sensor linear combination based on strong tracking filter is proposed. A four-degree of freedom vehicle nonlinear dynamics model and state estimation model including longitudinal,lateral and roll motion are established. With the estimator of multi-sensor information fusion and the strong tracking filter theory,the vehicle key states are simulated and analysed. The results show that the strong tracking filter offers higher performance potential. It can solve the problem that the state estimation values deviate from the true system states due to the model uncertainty and can inhibit the filtering divergence effectively. The technology of state estimation with the strong tracking filter has a wide range of adaptive tracking capability. It provides a real-time,accurate and low-cost soft-sensor way for vehicle advanced control.
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2009, Vol. 30 
