Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Intelligent Digital Redesign of a Fuzzy-Model-Based Controllers for Nonlinear Systems with Uncertainties

불확실성을 갖는 비선형 시스템을 위한 퍼지 모델 기반 제어기의 지능형 디지털 재설계

  • 장권규 (군산대학교 전자정보공학부) ;
  • 권오신 (군산대학교 전자정보공학부) ;
  • 주영훈 (군산대학교 전자정보공학부)
  • Published : 2006.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear system which may also contain system uncertainties. The continuous-time uncertain TS fuzzy model is first contructed to represent the uncertain nonlinear system. A parallel distributed compensation(PDC) technique is then used to design a fuzzy-model-based controller for both stabilization. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using a globally intelligent digital redesign method. This new technique is designed by a global matching of state variables between analog control system and digital control system. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear systems with uncertainties. Finally, Chaotic Lorenz system is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

Keywords

References

  1. W. Chang, Y. H. Joo, J. B. Park, 'Digital control of an inverted pendulum by using ingelligent digital redisign' 대한전기학회 논문지, vol. 50D, pp. 457-463, 2001, 10
  2. Y. H. Joo, Y. W. Lee, D. B. Cha, and J. H. Oh, Intelligent Digitally Redesigned Fuzzy Controller,' Int. Journal of Fuzzy logic and Intelligent Systems, vol. 2, no. 3, pp. 221-226, 2002, 12
  3. T. Takagi and M. Sugeno, 'Fuzzy identification of systems and its applications to modeling and control,' IEEE Transactions on Fuzzy Systems, vol. 15, pp. 116-132, 1985
  4. H. O. Wang, K. Tanaka, and M. Griffin, 'An approach of fuzzy control of nonlinear systems: stability and design issues,' IEEE Transactions on Fuzzy Systems, vol. 4, pp. 14-23, Feb. 1996 https://doi.org/10.1109/91.481841
  5. K. Tanaka, T. Ikeda, and H. O. Wang, 'Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, $H_{\infty}$, control theory, and linear matrix inequalities,' IEEE Transactions on Fuzzy systems, vol. 86, no. 3, pp. 279-288, 1997
  6. H. J. Lee, J. B. Park, and G. Chen, 'Robust fuzzy control of nonlinear systems with parametric uncertainties,' IEEE Transactions on Fuzzy Systems, 2000. (to be published) https://doi.org/10.1109/91.919258
  7. 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 Transactions on Fuzzy Systems, vol. 7, pp. 394-408, Aug. 1999 https://doi.org/10.1109/91.784199
  8. J. Li, D. Niemann and H. O. Wang, 'Parallel distributed compensation for Takagi-Sugeno fuzzy models: multi-objective controller design,' Proc. of ACC, pp. 1832-1836, San Diego, California, June, 1999 https://doi.org/10.1109/ACC.1999.786166
  9. K. Tanaka and M. Sugeno, 'Stability analysis and design of fuzzy control systems,' Fuzzy Sets and Systems, vol. 45, no. 2, pp. 134-156, 1992 https://doi.org/10.1016/0165-0114(92)90113-I
  10. K. L. Cho, Y. H. Joo and J. B. Park, 'Intelligent Digital Redesign for Dynamical Systems with Uncertainties,' 퍼지 및 지능시스템학회 논문지, 2003, vol. 13, no 6, pp. 667-672 https://doi.org/10.5391/JKIIS.2003.13.6.667