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Systematic analysis and design of fu...

Mann, George Kingsly Indrarajan.

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Systematic analysis and design of fuzzy logic controllers for process control.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Systematic analysis and design of fuzzy logic controllers for process control./
作者:	Mann, George Kingsly Indrarajan.
面頁冊數:	212 p.
附註:	Adviser: R. G. Gosine.
Contained By:	Dissertation Abstracts International61-03B.
標題:	Artificial Intelligence. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NQ47498
ISBN:	0612474984

Systematic analysis and design of fuzzy logic controllers for process control.
Mann, George Kingsly Indrarajan.

Systematic analysis and design of fuzzy logic controllers for process control. - 212 p.

Adviser: R. G. Gosine.

Thesis (Ph.D.)--Memorial University of Newfoundland (Canada), 1999.

This thesis presents a systematic study and analysis of fuzzy PID-type controllers with particular attention to process control. The work aims to remove the ad-hoc procedures and multi-dimensional complexity in the conventional fuzzy control designs and to present an analytical framework for the systematic design of fuzzy logic controllers.

ISBN: 0612474984Subjects--Topical Terms:

769149
Artificial Intelligence.

Systematic analysis and design of fuzzy logic controllers for process control.
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100 1 $a Mann, George Kingsly Indrarajan. $3 1256947
245 1 0 $a Systematic analysis and design of fuzzy logic controllers for process control.
300 $a 212 p.
500 $a Adviser: R. G. Gosine.
500 $a Source: Dissertation Abstracts International, Volume: 61-03, Section: B, page: 1492.
502 $a Thesis (Ph.D.)--Memorial University of Newfoundland (Canada), 1999.
520 $a This thesis presents a systematic study and analysis of fuzzy PID-type controllers with particular attention to process control. The work aims to remove the ad-hoc procedures and multi-dimensional complexity in the conventional fuzzy control designs and to present an analytical framework for the systematic design of fuzzy logic controllers.
520 $a The work investigates different fuzzy PID control structures including the conventional Mamdani-type controller. By expressing the fuzzy rules in different forms, each PID structure is distinctly identified. The rules are written in terms of the feed back error signals of a closed-loop control system. Therefore a general fuzzy PID controller output may be produced with three-, two- or one-input rule inference. The solution algorithm has the capability to generate the closed-form expressions to the general three-input fuzzy inference. The linear-like fuzzy output is used to identify the fuzzy PID actions in a dissociated form. The design of fuzzy controllers is then treated as a two-level tuning problem. The first level tunes the nonlinear PID gains and the second level tunes the linear PID gains. By assigning a minimum number of rules to each PID structure, the linear and nonlinear gains are explicitly presented. The tuning characteristics of each structure are evaluated with respect to their functional behaviours. The rule decoupled and one-input rule structures proposed in this thesis provide greater flexibility and better functional properties than the conventional fuzzy controllers.
520 $a Non-linearity analysis is used to assess and rank the different fuzzy systems for fuzzy control. The normalized fuzzy output characteristics are identified for two-point control. Thus, a performance criterion is developed to identify the non-linearity tuning properties of the fuzzy controllers. The min-max-gravity fuzzy reasoning has shown better nonlinear properties for fuzzy control applications. An alternative nonlinear control using spline-based functions is proposed. The geometrically based nonlinear controller has better nonlinear properties for PID control.
520 $a Linear PID controllers are analyzed in detail. The study is narrowed to process systems whose dynamics can be roughly approximated to first-order plus dead-time plant systems. The PID analysis covers the process systems having normalized time delay ranging from zero to any higher value. The time-domain-based analysis produces new PID tuning expressions for each case. The proposed tuning rules accommodate actuator saturation limits and avoid integral wind-up during the control. With the new tuning rules better performance is observed than with other commonly available tuning methods.
520 $a Fuzzy PID controllers are then evaluated for process control. A novel two-level tuning scheme is proposed for designing and tuning fuzzy controllers. The two-level tuning strategy uses the available linear control knowledge, and the resulting design always guarantees better performance than the linear controllers. Finally the two-level tuning is effectively implemented in a real time control problem. With the systematic two-level tuning, the fuzzy controllers are able to produce superior and improved performance to linear PID controllers. The design and tuning is simple and therefore the method can be extended to any process control problem. (Abstract shortened by UMI.)
590 $a School code: 0306.
650 4 $a Artificial Intelligence. $3 769149
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, System Science. $3 1018128
690 $a 0790
690 $a 0800
690 $a 0984
710 2 0 $a Memorial University of Newfoundland (Canada). $3 1017906
773 0 $t Dissertation Abstracts International $g 61-03B.
790 $a 0306
790 1 0 $a Gosine, R. G., $e advisor
791 $a Ph.D.
792 $a 1999
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NQ47498