NDLI: Control Performance Comparison between a Type-2 Fuzzy Controller and a Comparable Conventional Mamdani Fuzzy Controller

Content Provider	IEEE Xplore Digital Library
Author	Xinyu Du Hao Ying
Copyright Year	2007
Description	Author affiliation: Wayne State Univ., Detroit (Xinyu Du; Hao Ying)
Abstract	Control performance comparison between a type-1 fuzzy controller (Tl-FC) and a comparable type-2 fuzzy controller (T2-FC) was carried out using computer simulation. Our objective was to study whether T2 fuzzy control always had a control performance advantage over its Tl counterpart as claimed in some simulation-based reports. We used a genetic algorithm to optimize the Tl-FC and the T2-FCs that control process models of three different types (i.e., linear, linear with a time-delay, and nonlinear). Controllers' robustness against model parameter variation and capabilities of dealing with random noise were compared as well. The simulation results show that different settings result in different comparison outcomes: (1) the Tl-FC and the T2-FC performed (almost) identically, and (2) the T2-FC outperformed its Tl counterpart, and (3) the T1-FC was superior. These results are theoretically sensible because from the controllers' input-output mapping standpoint, their ability to produce continuous nonlinear control functions should be similar and no inherent advantage likely exists. Thus, one controller can appear to be better than, worse than, or equal to its counterpart depending on the specific configuration of the whole control system. Consequently, no one should claim that T2 fuzzy control is generally better than T1 fuzzy control.
Starting Page	100
Ending Page	105
File Size	389418
Page Count	6
File Format	PDF
ISBN	1424412137
DOI	10.1109/NAFIPS.2007.383819
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy control Fuzzy sets Control systems Nonlinear control systems Fuzzy systems Robust control Mobile robots Process control Noise robustness Uncertainty
Content Type	Text
Resource Type	Article

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