Controller decision making using neural networks

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.