Based on Neural Network PID Controller Design and Simulation

Abstract:

The technologic of PID control is very conventional. There is an extensive application in many fields at present. The PID controller is simple in structure, strong in robustness, and can be understood easily. Then neural networks have great capability in solving complex mathematical problems since they have been proven to approximate any continuous function as accurately as possible. Hence, it has received considerable attention in the field of process control. Due to the complication of modern industrial process and the increase of nonlinearity, time-varying and uncertainty of the practical production processes, the conventional PID controller can no longer meet our requirement. This paper introduces the theoretical foundation of the BP neural network and studying algorithm of the neural network briefly, and designs the PID temperature control system and simulation model based on BP neural network.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 514-517
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.514
• Online since: September 2013
• Authors: Hao Xu, Jin Gang Lai, Zhen Hong Yu, Jiao Yu Liu
• Keywords: BP Neural Network (BPNN), PID Controller, Temperature Control System

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