전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제59권5호
  • /
  • Pages.972-980
  • /
  • 2010
  • /
  • 1975-8359(pISSN)
  • /
  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지
DOI QR코드

DOI QR Code

최적 퍼지 직렬형 제어기 설계: Type-2 퍼지 제어기 및 공정경쟁기반 유전자알고리즘을 중심으로

The Design of Optimized Fuzzy Cascade Controller: Focused on Type-2 Fuzzy Controller and HFC-based Genetic Algorithms

  • 김욱동 (수원대 공대 전기공학과) ;
  • 장한종 (수원대 공대 전기공학과) ;
  • 오성권 (수원대 공대 전기공학과)
  • 투고 : 2009.10.09
  • 심사 : 2010.03.19
  • 발행 : 2010.05.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.

키워드

참고문헌

  1. H. J. Lee, J. B. Park and G. Chen, "Robust Fuzzy Control of Nonlinear Systems with Parametric Uncertainties," IEEE Trans. on Syst., Vol. 9, No. 2, pp. 369-379, 2001.
  2. H.-N. Wu and K.-Y. Cai, "Robust fuzzy control for uncertain discrete-time nonlinear Markovian jump systems without mode observations," Information Sciences Vol. 177, Issue 6, pp. 1509-1522, 2007. https://doi.org/10.1016/j.ins.2006.07.031
  3. Dongrui Wu and Woei Wan Tan, "Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers", Engineering applications of Artificial Intelligence, Vol. 19, Issue 8, pp. 829-841, 2006 https://doi.org/10.1016/j.engappai.2005.12.011
  4. Zadeh, L. A., "The concept of a linguistic variable and its application to approximate reasoning-1", Information Sciences 8, Issue 3, pp. 199-249, 1975 https://doi.org/10.1016/0020-0255(75)90036-5
  5. D. Wu and W. Tan, "Type-2 fuzzy logic controller for the liquid-level process", Proceeding of the 2004 IEEE International Conference on Fuzzy Ststems, pp. 248-253, Budapest, Hungary, 2004.
  6. Hagras H. A., "A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots", IEEE Trans. Fuzzy Syst. Vol. 12, pp. 524-539, 2004. https://doi.org/10.1109/TFUZZ.2004.832538
  7. Liang Q. and Mendel J. M., "MPEG VBR video traffic modelling and classification using fuzzy technique. IEEE Trans. Fuzzy Syst., Vol. 9, pp. 183-193, 2001. https://doi.org/10.1109/91.917124
  8. S.-K. Oh, W. Pedrycz, S.-B. Rho and T.-C. Ahn, "Parameter estimation of fuzzy controller and Its application to inverted pendulum" Engineering Applications of Artificial Intelligence, Vol. 17, Issue 1, February 2004, Pages 37-60. https://doi.org/10.1016/j.engappai.2003.12.003
  9. J.-N. Choi, S.-K. Oh and K.-S. Seo, "Simultaneous Optimization of ANFIS-Based Fuzzy Model Driven to Data Granulation and Parallel Genetic Algorithms," LNCS, Vol. 4493, pp. 225-230, 2007.
  10. C. C. Hang, K. J. Astrom and Q. G. Wang, "Relay feedback auto-tuning of process controllers-a tutorial review", Journal of Process Control, Vol. 12, Issue 1, pp 143-162, 2002. https://doi.org/10.1016/S0959-1524(01)00025-7
  11. Sung-Kuwn Oh, Seung-Hyun Jung, and Witold Pedrycz, "Design of Optimizaed Fuzzy Cascade controller by Means of Hierarchical Fair Competition-based Genetic Algorithms", Expert Systems With Applications(ESWA), Vol. 36, No. 9, pp.11641-11651, Nov 2009. https://doi.org/10.1016/j.eswa.2009.03.027
  12. K.K. Ahn, K.Q. Truong, " Online tuning fuzzy PID controller using robust extended Kalman filter", Journal of Process Control, Vol.19, No.6, pp.1011-1023, June 2009. https://doi.org/10.1016/j.jprocont.2009.01.005
  13. Juing-Shian Chiou, Ming-Tang Liu, " Numerical simulation for Fuzzy_PID controllers and helping EP reproduction with PSO hybrid algorithm," Simulation Modeling Practice and Theory, Vol.17, No.10, pp.1555-1564, Nov 2009. https://doi.org/10.1016/j.simpat.2009.05.006
  14. Cheng Liu, Jin-Feng Peng, Fu-Yu Zhao, Chong Li," Design and optimization offuzzy-PID controller for the nuclear reactor power control," Nuclear Engineering and Design, Vol.239, No.11, pp.2311-2316, Nov 2009. https://doi.org/10.1016/j.nucengdes.2009.07.001
  15. Kuan-Yu Chen, Pi-Cheng Tung, Mong-tao Tsai, Yi-Hua Fan, " A self-tuning fuzzy PID-type controller design for unbalance compensation in an active magnetic bearing," Expert Systems with https://doi.org/10.1016/j.eswa.2008.10.055