Ant colony optimization algorithm and its application to Neuro-Fuzzy controller design |
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Authors: | Zhao Baojiang Li Shiyong |
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Affiliation: | 1. Dept.of Control Science and Engineering,Harbin Inst.of Technology,Harbin 150001,P.R.China;Dept.of Mathematics,Mudanjiang Teachers Coll.,Mudanjiang 157012,P.R.China 2. Dept.of Control Science and Engineering,Harbin Inst.of Technology,Harbin 150001,P.R.China |
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Abstract: | An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information.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,a state variable synthesis scheme is emploved to reduce the number of fuzzy rules greatly.The simulation results show that the designed controller can control the inverted pendulum successfully. |
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Keywords: | neuro-fuzzy controller ant colony algorithm function optimization genetic algorithm inverted pendulum system. |
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