Simulation Design of Fuzzy Logic System Without Any Rules Based on Fuzzy Perception Intensity

LI Yujiao; WANG Yinhe

doi:10.11999/JEIT170583

Volume 40 Issue 4

Apr. 2018

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LI Yujiao, WANG Yinhe. Simulation Design of Fuzzy Logic System Without Any Rules Based on Fuzzy Perception Intensity[J]. Journal of Electronics & Information Technology, 2018, 40(4): 979-874. doi: 10.11999/JEIT170583

Citation:

LI Yujiao, WANG Yinhe. Simulation Design of Fuzzy Logic System Without Any Rules Based on Fuzzy Perception Intensity[J]. Journal of Electronics & Information Technology, 2018, 40(4): 979-874. doi: 10.11999/JEIT170583

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Simulation Design of Fuzzy Logic System Without Any Rules Based on Fuzzy Perception Intensity

doi: 10.11999/JEIT170583

LI Yujiao¹,
WANG Yinhe²

1.
(Guangzhou College, South China University of Technology, Guangzhou 510800, China)
2.
(School of Automation, Guangdong University of Technology, Guangzhou 510006, China)

Funds:

The National Natural Science Foundation of China (61673120)

Received Date: 2017-06-15
Rev Recd Date: 2017-12-14
Publish Date: 2018-04-19

Abstract

Abstract

Based on the effectiveness of the fuzzy logic in the field of psychological linguistics research, this paper proposes a new kind of fuzzy logic system without any rules based on fuzzy perception intensity and Webers law, and the method of adaptive control application. Firstly, applying the concept of psychophysics, the knowledge base of fuzzy logic system is constructed by fuzzy perception intensity, which describes experts experience feelings. After fuzzy reasoning, the final output is obtained from defuzzification by generalized Weber's law. Secondly, for a class of nonlinear system, this new fuzzy logic system is adopted to design adaptive controller and parameters adaptive laws. Finally, the feasibility and validity of the method are illustrated through the synchronization simulation about Duffing chaotic systems.
- Fuzzy perception intensity,
- Webers law,
- Fuzzy logic system without any rules,
- Duffing chaotic systems,
- Adaptive control

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References(22)

References

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