Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (4): 911-915.

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Online optimization design of fuzzy controllers based on hierarchic genetic algorithm

LI Hua, MA Qiu   

  1. School of Automation & Electrical Engineering, Lanzhou Jiaotong Univ., Lanzhou 730070, China
  • Received:2008-02-01 Revised:2008-05-11 Online:2009-04-20 Published:2010-01-03

Abstract: Aiming at the problem of optimization of fuzzy controllers,a method of online optimization design based on the improved hierarchic genetic algorithm is proposed.The method modifies the information exchange style on the basis of hierarchic genetic algorithm.Using and improving the adaptive crossover operator and mutation operator,the genetic algorithm has better local search ability based upon current optimal solutions,so the search speed and search precision of genetic algorithm are increased.Meanwhile,by using restricted integration performance index ITAE,the optimization can be emphasized particularly on the steady-state error,the overshoot or the rise time.By introducing the LS parameter online identification,the parameters and structure of fuzzy controllers can be fast optimized simultaneously in the time-delay and time-varying system.Simulation experiments illustrate the validity of the proposed method.

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