Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Decentralized Control Technique for Experimental Nonlinear Helicopter Systems

헬리콥터 시스템의 퍼지 분산 제어기 설계

  • Kim, Moon-Hwan (Dept. of Electronic Eng., Yonsei Univ. Seoul, 139-221, Korea) ;
  • Park, Jin-Bae (Dept. of Electronic Eng., Yonsei Univ. Seoul, 139-221, Korea) ;
  • Lee, Ho-Jae (Dept. of Electronic Eng., Yonsei Univ. Seoul, 139-221, Korea) ;
  • Cha, Dae-Bum (School of Electronic and Imformation Eng., Kunsan National Univ. Kunsan, chonbuk) ;
  • Joo, Young-Hoon (School of Electronic and Imformation Eng., Kunsan National Univ. Kunsan, chonbuk)
  • Published : 2002.02.01
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Abstract

This paper proposes a decentralized control technique for 2-dimensional experimental helicopter systems. The decentralized control technique is especially suitable in large-scale control systems. We derive the stabilization condition for the interconnected Takagi-Sugeno (TS) fuzzy system using the rigorous tool-Lyapunov stability criterion and formulate the controller design condition in terms of linear matrix inequality (LMI). To demonstrate the feasibility of the proposed method, we include the experiment result as well as a computer simulation one, which strongly convinces us the applicability to the industry.

본 논문은 2자유도 실험용 헬리콥터 시스템의 제어를 위한 분산 제어기 설계 기법을 제안한다. 분산제어기법은 특히 대규모 제어 시스템에 적합하다고 알려져 있다. 본 논문에서는 Lyapunov 안정도 설계 방법을 이용하여 상호 연결된 TS 퍼지 시스템의 안정도 조건을 유도하고 선형 행렬 부등식을 이용하여 제어기 설계 조건을 공식화한다. 제안된 방법의 유용성을 검증하기 위해, 컴퓨터 시뮬레이션뿐 만 아니라 실험을 통해 그 결과를 도출한다.

Keywords

References

  1. M. Akar and Uozguner, "Decentralized techniques for the analysis and control of Takagi-Sugeno fuzzy systems," IEEE Trans. on Fuzzy Systems, vol. 8, no. 6, pp. 691-704, Dec., 2000. https://doi.org/10.1109/91.890328
  2. H. J. Lee, J. B. Park and G. Chen, "Robust fuzzy control of nonlinear systems with parametric uncertainties," IEEE Trans. on Fuzzy Systems, vol. 9, no. 2, pp. 369-379, April, 2001. https://doi.org/10.1109/91.919258
  3. W. Chang, J. B. Park, Y. H. Joo, and G. Chen, "Design of robust fuzzy-model-based controller with sliding mode control for SISO nonlinear systems," Fuzzy Sets and Systems, to appear, 200l.
  4. Y. H. Joo, G. Chen, and L. S. Shieh, "Hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems," IEEE Trans. on Fuzzy Systems, vol. 7, pp. 394-408, Aug, 1999. https://doi.org/10.1109/91.784199
  5. W. Chang, J. B. Park, Y. H. Joo, and G. Chen, "Design of sampled-data fuzzy-model-based control systems by using intelligent digital redesign," IEEE Trans. on eirc. and Syst. -1, to appear, 200l.
  6. Z. Li, J. B. Park, and Y. H Joo "Chaotifying continuous-time TS fuzzy systems via discretization," IEEE Trans. on Circ. and Syst. -1, vol. 48, no. 10, pp. 1237-1243, 2001. https://doi.org/10.1109/81.956020
  7. K. Tanaka, T. Ikeda, and H. O. Wang, "Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs," IEEE Trans. on Fuzzy Systems, vol. 6, no. 2, pp. 250-265, 1998. https://doi.org/10.1109/91.669023
  8. G. Feng, "Approaches to quadratic stabilization of uncertain fuzzy dynamic systems," IEEE Trans. on Circ. and Syst.-l, vol. 48, no. 6, pp. 760-779, 2001. https://doi.org/10.1109/81.928159

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