Controller decision making using neural networks

Most industrial processes contain nonlinearities, making them difficult to control. To overcome this issue many authors have developed complex nonlinear algorithms and models, most of them being process dependant. However, creating local models to approximate the plant by linear regions is a suita...

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Bibliographic Details
Main Author: Andres Prado Espinoza
Other Authors: Mao Kezhi
Format: Theses and Dissertations
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10356/41420
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Institution: Nanyang Technological University
Language: English
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Summary:Most industrial processes contain nonlinearities, making them difficult to control. To overcome this issue many authors have developed complex nonlinear algorithms and models, most of them being process dependant. However, creating local models to approximate the plant by linear regions is a suitable approach in most cases. This approach lets the engineer create local PID controllers and switch them according to the plant linear regions.