T-S norm FNN controller based on hybrid learning algorithm
GUO Bing-jie, LI Yue-ming, Wan Lei
College of Shipbuilding Engineering,Harbin Engineering University,Harbin 150001,China
Abstract:
Aiming at the problems that fuzzy neural network controller has heavy computation and lag,a T-S norm Fuzzy Neural Network Control based on hybrid learning algorithm was proposed.Immune genetic algorithm (IGA) was used to optimize the parameters of membership functions (MFs) off line,and the neural network was used to adjust the parameters of MFs on line to enhance the response of the controller.Moreover,the latter network was used to adjust the fuzzy rules automatically to reduce the computation of the neural network and improve the robustness and adaptability of the controller,so that the controller can work well ever when the underwater vehicle works in hostile ocean environment.Finally,experiments were carried on " XX" mini autonomous underwater vehicle (min-AUV) in tank.The results showed that this controller has great improvement in response and overshoot,compared with the traditional controllers.
Key words: T-S norm fuzzy neural network Underwater vehicles Immune genetic algorithm Hybrid learning algorithm
DOI：10.11916/j.issn.1005-9113.2011.03.006
Clc Number:TP273
Fund:
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T-S norm FNN controller based on hybrid learning algorithm
本站小编 哈尔滨工业大学/2019-10-23
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