Frontiers of Information Technology & Electronic Engineering
>> 2016,
Volume 17,
Issue 6
doi:
10.1631/FITEE.1601019
Derivation and analysis on the analytical structure of interval type-2 fuzzy controller with two nonlinear fuzzy sets for each input variable Project supported by the Xinjiang Astronomical Observatory, China (No. 2014KL012), the Major State Basic Research Development Program of China (No. 2015CB857100), the National Natural Science Foundation of China (Nos. 51490660 and 51405362), and the Fundamental Research Funds for the Central Universities, China (No.SPSY021401)
. MOE Key Laboratory of Electronic Equipment Structure Design, Xidian University, Xi’an 710071, China.. Xinjiang Observatory, National Astronomical Observatories, Chinese Academy of Sciences, Urumqi 830011, China
Available online: 2016-06-28
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Abstract
Type-2 fuzzy controllers have been mostly viewed as black-box function generators. Revealing the analytical structure of any type-2 fuzzy controller is important as it will deepen our understanding of how and why a type-2 fuzzy controller functions and lay a foundation for more rigorous system analysis and design. In this study, we derive and analyze the analytical structure of an interval type-2 fuzzy controller that uses the following identical elements: two nonlinear interval type-2 input fuzzy sets for each variable, four interval type-2 singleton output fuzzy sets, a Zadeh AND operator, and the Karnik-Mendel type reducer. Through dividing the input space of the interval type-2 fuzzy controller into 15 partitions, the input-output relationship for each local region is derived. Our derivation shows explicitly that the controller is approximately equivalent to a nonlinear proportional integral or proportional differential controller with variable gains. Furthermore, by comparing with the analytical structure of its type-1 counterpart, potential advantages of the interval type-2 fuzzy controller are analyzed. Finally, the reliability of the analysis results and the effectiveness of the interval type-2 fuzzy controller are verified by a simulation and an experiment.
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