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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2949

Title: Heuristic on-line tuning for nonlinear model predictive controllers using fuzzy logic
Authors: Ali, Emad
Keywords: Model predictive control
Online tuning
Fuzzy logic
Performance specification
Issue Date: 2003
Publisher: Elsevier B.V.
Citation: J Process Control: 13 (5); 383-396
Abstract: In this paper a systematic mechanism for online tuning of the nonlinear model predictive controllers is presented. The proposed method automatically adjusts the prediction horizon, P, the diagonal elements of the input weight matrix, Λ, and the diagonal elements of the output weight matrix, Γ for the sake of good performance. The desired good performance is cast as a time-domain specification. The control horizon, M is left constant because its relative value with respect to P is more important. The tuning algorithm is designed using the fuzzy logic concepts. Predefined fuzzy rules that represent available tuning guidelines and the performance violation measure in the form of fuzzy sets determine the new tuning parameter values. Therefore, the tuning algorithm is formulated as a simple and straightforward mechanism. This feature makes it more appealing for online implementation. The effectiveness of the proposed tuning method is tested through simulated implementation on three nonlinear process examples. Two of these examples possess open-loop unstable dynamics. The result of the simulations revealed the success of such a method.
Description: Corresponding Author: Mr. Emad Ali Chemical Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia. Fax: +966-1-467-8770, Email: amkamal@ksu.edu.sa
URI: http://hdl.handle.net/123456789/2949
Appears in Collections:College of Engineering

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