OS16-5 Simulation of PID Temperature Control System Based on Neural Network

Title:	OS16-5 Simulation of PID Temperature Control System Based on Neural Network
Publication:	ICAROB2018
Volume:	23
Pages:	637-640
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2018.OS16-5
Author(s):	Yujie Yan, Fengzhi Dai, Lingran An, Yuxing Ouyang, Zhongyong Ye, Xia Jin, Ce Bian
Publication Date:	February 2, 2018
Keywords:	neural network, PID control, MATLAB, temperature
Abstract:	The system designed in this paper is a combination of neural network and PID control. BP neural network has a great advantage in solving the control of nonlinear and uncertain systems. It can use the steepest descent learning method to adjust the threshold and weight values by back propagation. The ultimate goal is to adjust the PID controller adjustable parameters by the neural network learning algorithm. Using MATLAB software to simulate, the results show that the system has a strong following performance and a high anti-interference ability. Experiments show that the PID temperature control system based on neural network has some practicality.
PDF File:	https://alife-robotics.co.jp/members2018/icarob/data/html/data/OS_pdf/OS16/OS16-5.pdf
Copyright:	© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/