Research On Fuzzy Control Algorithm And Its Application To Navigation System

The proper selection of fuzzy rules, which determines the performance and learning ability, is the key problem of the adaptive fuzzy control system. Through the research on the combination of fuzzy control and genetic algorithm, a new optimized algorithm based on decimal-code is provided, which unites the membership functions and fuzzy control rules into integrated one for whole-scope searching, and the operators of genetic algorithm is modulated fit for the change of the code. Secondly, the thesis is focused on the kalman filter in GPS/INS integrated navigation system and a new method that uses fuzzy controller for adjusting the kalman filter is proposed. The simulation results indicated that fuzzy kalman filter was better than the kalman filter. However the parameters of fuzzy algorithm with subjectivity and arbitrariness are determined by the expert experience. Therefore, the fuzzy kalman filter was optimized using the modified genetic algorithm and the simulation results proved the validity of the algorithm.