Intelligent Adaptive Filtering Algorithm Based on Fuzzy Control Optimized by Genetic Algorithm

Since the soft fault was difficult to be detected,Kalman filter used in the integrated navigation system tended to appear a drastic declining of accuracy,or even a divergence.Therefore,an intelligent adaptive filtering algorithm based on fuzzy control optimized by genetic algorithm was proposed in order to improve the fault-tolerant ability of filter.Firstly,a fuzzy adaptive filtering algorithm was presented to deal with the soft fault.By monitoring the residual and its rate,the observation quality gene was obtained by the fuzzy control system and the filtering measurement noise matrix was adaptively adjusted on-line.The filtering effects arising from the gradual changing fault could be prevented to a large extent,and then a nice filtering accuracy and improved fault-tolerant ability were achieved.The adaptive genetic algorithm was applied to optimize the membership functions so as to enhance the entire accuracy of algorithm.At last,the proposed algorithm was used to develop a positioning experiment based on a SINS/CNS/GPS integrated navigation platform.The results show that the proposed algorithm is valid,and the positioning accuracy is less than 2 m and the velocity accuracy is less than 0.1 m/s while the soft fault exists.