NDLI: Optimal design of neuro-fuzzy controller based on ant colony algorithm

Content Provider	IEEE Xplore Digital Library
Author	Zhao Baojiang
Copyright Year	2010
Description	Author affiliation: Department of Mathematics, Mudanjing Teachers College, Heilongjiang 157012, China (Zhao Baojiang)
Abstract	An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of the trail information updating. The algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. The results of function optimization show that the algorithm has good searching ability and high convergence speed. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due to multivariable inputs, state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. The simulation results show that the designed controller can control the inverted pendulum successfully.
Starting Page	2513
Ending Page	2518
File Size	141808
Page Count	6
File Format	PDF
ISBN	9781424462636
e-ISBN	9787894631046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Association of Aut
Subject Keyword	Algorithm design and analysis Ant Colony Algorithm Neuro-Fuzzy Controller Heuristic algorithms Simulation Artificial neural networks Inverted Pendulum System Genetic Algorithm Noise measurement Optimization Function Optimization Convergence
Content Type	Text
Resource Type	Article

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