中国物理B ›› 2005, Vol. 14 ›› Issue (1): 67-71.doi: 10.1088/1009-1963/14/1/014

• GENERAL • 上一篇    下一篇

Chaotifying a stable Takagi-Sugeno fuzzy system by a sawtooth nonlinearity

卢俊国   

  1. Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China
  • 收稿日期:2004-05-26 修回日期:2004-09-06 出版日期:2005-01-20 发布日期:2005-01-20
  • 基金资助:
    Project supported by the National Postdoctoral Science Foundation of China and the National Natural Science Foundation of China (Grant No 60404005).

Chaotifying a stable Takagi-Sugeno fuzzy system by a sawtooth nonlinearity

Lu Jun-Guo (卢俊国)   

  1. Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China
  • Received:2004-05-26 Revised:2004-09-06 Online:2005-01-20 Published:2005-01-20
  • Supported by:
    Project supported by the National Postdoctoral Science Foundation of China and the National Natural Science Foundation of China (Grant No 60404005).

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摘要： The problem of making a stable Takagi--Sugeno (TS) fuzzy system chaotic by using the state feedback control of arbitrarily small magnitude is studied. The feedback controller used is a simple sawtooth function of the system state.The improved Marotto theorem has been obtained and applied to mathematically prove that the controlled system is chaotic in the sense of Li and Yorke. In particular, an explicit formula for the computation of chaotification parameters is obtained. A numerical example is used to visualize and illustrate the theoretical results.

Abstract: The problem of making a stable Takagi--Sugeno (TS) fuzzy system chaotic by using the state feedback control of arbitrarily small magnitude is studied. The feedback controller used is a simple sawtooth function of the system state.The improved Marotto theorem has been obtained and applied to mathematically prove that the controlled system is chaotic in the sense of Li and Yorke. In particular, an explicit formula for the computation of chaotification parameters is obtained. A numerical example is used to visualize and illustrate the theoretical results.

Key words: chaos, chaotification, TS fuzzy system, chaos control

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  • 0545