A two-stage design of adaptive fuzzy controllers for time-delay systems with unknown models

In this article, a systematic two-stage design method for adaptive fuzzy controllers is presented. The proposed control scheme has low computational complexity. Moreover, the exact mathematical model of the plant to be controlled is not required. The fuzzy controller under consideration is based on...

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Published in:International journal of systems science 2007-01, Vol.38 (5), p.433-449
Main Authors: Taur, J. S., Lee, G. H., Tao, C. W.
Format: Article
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Control system synthesis
Control theory. Systems
Exact sciences and technology
Fuzzy controller
If > then rule
System theory
Triangular membership function
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description In this article, a systematic two-stage design method for adaptive fuzzy controllers is presented. The proposed control scheme has low computational complexity. Moreover, the exact mathematical model of the plant to be controlled is not required. The fuzzy controller under consideration is based on the proportional-derivative fuzzy control scheme and triangular membership functions. In the design procedure, the domain intervals of the input and output variables are selected with a heuristic approach to minimize a cost function under the constraint of tolerable overshoots in the response curve. A learning scheme is then proposed to automatically adjust the parameters in the fuzzy controller to reduce the error of the system. It can also be used adaptively to improve the system performance of a time-varying system. Simulations and comparisons are included to demonstrate the effectiveness of the proposed method.
doi_str_mv 10.1080/00207720701276481
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subjects Applied sciences
Computer science
control theory
systems
Control system synthesis
Control theory. Systems
Exact sciences and technology
Fuzzy controller
If--then rule
System theory
Triangular membership function
title A two-stage design of adaptive fuzzy controllers for time-delay systems with unknown models
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