Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Design of T-S Fuzzy-Model-Based Controller for Control of Autonomous Underwater Vehicles

무인 잠수정의 심도 제어를 위한 T-S 퍼지 모델 기반 제어기 설계

  • Received : 2011.03.19
  • Accepted : 2011.05.01
  • Published : 2011.06.25
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents Takagi-Sugeno (T-S) fuzzy-model-based controller for depth control of autonomous underwater vehicles(AUVs). Through sector nonlinearity methodology, The nonlinear AUV is represented by T-S fuzzy model. By using the Lyapunov function, the design condition of controller is derived to guarantee the performance of depth control in the format of linear matrix inequality (LMI). An example is provided to illustrate the effectiveness of the proposed methodology.

본 논문은 무인 잠수정(Autonomous underwater vehicles: AUVs)의 심도 제어를 위한 타카키-수게노 (Takagi-Sugeno: T-S) 퍼지 모델 기반 제어기를 제안한다. Sector nonlinearity 기법을 통해 주어진 비선형 무인 잠수정은 T-S 퍼지 모델로 표현된다. 리아푸노프(Lyapunov) 함수를 이용하여 무인 잠수정의 심도 제어 성능을 보장하는 선형 행렬 부등식(Linear matrix inequality: LMI) 형태의 제어기 설계 조건을 유도한다. 모의 실험을 통해 제안된 기법의 심도 제어 성능을 검증한다.

Keywords

References

  1. T. Prestero, "Verification of a six-degree of freedom simulation model for the REMUS autonomous underwater vehicle," Masters Thesis, Department of Ocean Engineering and Mechanical Engineering, MIT, USA, 2001.
  2. T. I. Fossen, Guidance and Control of Ocean Vehicles. Wiley, New York, 1994.
  3. J. H. Li and P. M. Lee, "Design of adaptive nonlinear controller for depth control of an autonomous underwater vehicle," Ocean Engineering. vol. 32, no. 17-18, pp. 2165-2181, 2005. https://doi.org/10.1016/j.oceaneng.2005.02.012
  4. L. Lapierre, "Robust diving control of an AUV," Oceanic Engineering, vol. 36, no. 1, pp. 92-104, 2005.
  5. A. J. Healey and D. Lienard, "Multivariable sliding mode control for autonomous diving and stee- ring of unmanned underwater vehicles," Ocean Engineering, vol. 18, no. 3, pp-327-339.
  6. K. Tanaka and H. O. Wang, "Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach," New York: Wiley, 2001.
  7. D. W. Kim, H. J. Lee, and M. Tomizuka, "Fuzzy stabilization of nonlinear systems under sampleddata feedback: an exact discrete-time model ap- proach," IEEE Trans. fuzzy syst., pp. 251-260, vol. 18, no. 2, 2010. https://doi.org/10.1109/TFUZZ.2010.2040184
  8. D. W. Kim and H. J. Lee, "stability connection between sampled-data fuzzy control systems with quantization and their approximate discrete-time model," Automatica, vol. 45, no. 6, pp. 1518-1523, 2009. https://doi.org/10.1016/j.automatica.2009.02.009
  9. D. W. Kim, J. B. Park, and Y. H. Joo, "Theoretical justification of approximate norm minimization method for intelligent digital redesign," Automatica, vol. 44, no. 3, pp. 851-856, 2008. https://doi.org/10.1016/j.automatica.2007.07.003
  10. D. W. Kim, J. B. Park, and Y. H. Joo, "Effective digital implementation of fuzzy control systems based on approximate discrete-time models," Automatica, vol. 43, no. 10, pp. 1671-1683, 2007. https://doi.org/10.1016/j.automatica.2007.01.025

Cited by

  1. DSSS-based Channel Access Technique DS-CDMA for Underwater Acoustic Transmission vol.15, pp.1, 2015, https://doi.org/10.5391/IJFIS.2015.15.1.53
  2. Sampled-Data Controller Design for Nonlinear Systems Including Singular Perturbation in Takagi-Sugeno Form vol.26, pp.1, 2016, https://doi.org/10.5391/JKIIS.2016.26.1.050
  3. Design of Buoyancy and Moment Controllers of a Underwater Glider Based on a T-S Fuzzy Model vol.65, pp.12, 2016, https://doi.org/10.5370/KIEE.2016.65.12.2037