Design of Adaptive Fuzzy Logic Controller for SVC using Tabu Search and Neural Network

Tabu 탐색법과 신경회로망을 이용한 SVC용 적응 퍼지제어기의 설계

  • 손종훈 (부산대 전기공학과 석사) ;
  • 황기현 (부산대 컴퓨터 및 정보통신연구소 기금) ;
  • 김형수 (부산대 전기공학과 박사) ;
  • 박준호 (부산대 전기공학과) ;
  • 박종근 (서울대 전기공학과)
  • Published : 2002.04.01

Abstract

We proposed the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gains of input-output variables of fuzzy logic controller(FLC) and weights of neural network using Tabu search. Neural network was used for adaptively tuning the output gain of FLC. The weights of neural network was learned from the back propagation algorithm in real-time. To evaluate the usefulness of AFLC, we applied the proposed method to single-machine infinite system. AFLC showed the better control performance than PD controller and GAFLS[10] for three-phase fault in nominal load which had used when tuning AFLC. To show the robustness of AFLC, we applied the proposed method to disturbances such as three-phase fault in heavy and light load. AFLC showed the better robustness than PD controller and GAFLC[10].

Keywords

References

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