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01453 am a22001693u 4500 |
| 001 |
40389 |
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|a dc
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| 100 |
1 |
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|a Al Gizi, Abdullah J. H.
|e author
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| 700 |
1 |
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|a Mustafa, Mohd. Wazir
|e author
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| 700 |
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|a A. Alsaedi, Malik
|e author
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| 700 |
1 |
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|a Zreen, N.
|e author
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| 245 |
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|a Fuzzy control system review
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| 260 |
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|c 2013.
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| 856 |
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|z Get fulltext
|u http://eprints.utm.my/id/eprint/40389/1/AbdullahJH2013_FuzzyControlSystemReview.pdf
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|a Overall intelligent control system which runs on fuzzy, genetic and neural algorithm is a promising engine for large -scale development of control systems . Its development relies on creating environments where anthropomorphic tasks can be performed autonomously or proactively with a human operator. Certainly, the ability to control processes with a degree of autonomy is depended on the quality of an intelligent control system envisioned. In this paper, a summary of published techniques for intelligent fuzzy control system is presented to enable a design engineer choose architecture for his particular purpose. Published concepts are grouped according to their functionality. Their respective performances are compared. The various fuzzy techniques are analyzed in terms of their complexity, efficiency, flexibility, start-up behavior and utilization of the controller with reference to an optimum control system condition.
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| 546 |
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|a en
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|a TK Electrical engineering. Electronics Nuclear engineering
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