Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2759

Full Length Research Paper

A review of modeling errors and control for time-delay systems utilizing the LDI criterion

Pei-Yin Chung1, Han-Chung Yang2, Cheng-Wu Chen3,4 and Chin-Jui Chang5*
1Department of Information Management, Meiho University, 23, Pingguang Rd., Neipu, Pingtung, Taiwan, R.O.C. 2Department of Leisure, Recreation and Tourism Management, Shu-Te University, Kaohsiung, Taiwan, R.O.C. 3Institute of Maritime Information and Technology, National Kaohsiung Marine University, Kaohsiung 80543, Taiwan, R.O.C. 4Global Earth Observation and Data Analysis Center (GEODAC), National Cheng Kung University, No. 1, Ta-Hsueh Road, Tainan 701, Taiwan, R.O.C. 5Department of Information Management, Transworld University, No. 1221, Jen-Nang Road, Chia-Tong Li, Douliou, Yunlin 64063, Taiwan, R.O.C.
Email: [email protected]

  •  Accepted: 08 November 2011
  •  Published: 16 January 2012


Nonlinear systems sometimes suffer from modeling errors which could potentially result in instability and reduce the control performance of the actual systems. This paper reviews some previous research studies examining the sources of these errors and how to deal with them. In this work, a fuzzy Lyapunov function is defined through fuzzy blending quadratic Lyapunov functions to avoid conservatism in the stability conditions. Therefore, the neural network (NN) model based approach is provided and the fuzzy systems can be transferred into a linear difference inclusion (LDI) formulation. Time-delay stability conditions of closed-loop controlled systems are then derived based on robustness design to deal with the modeling error problems.


Key words: Fuzzy Lyapunov method, LDI, T-S fuzzy systems, artificial intelligence.