Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/41420
Title: Controller decision making using neural networks
Authors: Andres Prado Espinoza
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
Issue Date: 2008
Abstract: 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.
URI: http://hdl.handle.net/10356/41420
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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