Optimal Design of Neuro-Fuzzy Controller Based on Ant Colony Algorithm

摘要：

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.

关键词： Neuro-Fuzzy Controller Ant Colony Algorithm Function Optimization Genetic Algorithm Inverted Pendulum System

作者: ZHAO Baojiang

作者单位: Department of Mathematics, Mudanjing Teachers College, Mudanjing Heilongjiang 157012, P. R. China

会议类型: 国际会议

会议名称: The 29th Chinese Control Conference(第二十九届中国控制会议)

会议地点: 北京

会议语种:英文

页码: 1-6

在线出版日期: 2010-07-29（万方平台首次上网日期，不代表论文的发表时间）