A Research on Information Collection Method for High-Precision Temperature Based on PLC Control

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Abstract:

For the traditional PID algorithm, it is difficult to give a precise mathematical model which makes parameters setting of PLC temperature control system difficult. At the same time there are some defects in the system control, resulting in low system security, reliability and control quality. In order to solve the problems of the traditional algorithms, this paper proposes an information collection algorithm for temperature denoising based on high-precision PLC control, which is a combination of the PID algorithm, fuzzy control algorithms and neural network algorithm. Experiments show that the algorithm is effective to achieve the parameters self-tuning of PID, increase the accuracy of the temperature control, and are practical in the PLC temperature control system.

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148-152

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June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Shunzhou Yu, Xiaodong Xu, An Input and Output Monitoring System for FPGA-based Hardware PLC, IJEI, Vol. 3, No. 1, p.34 ~ 44, (2012).

DOI: 10.4156/ijei.vol3.issue1.4

Google Scholar

[2] Wang Wenjiang, Sun Huilai, Lin Shuzhong, Chen Jun, Failure Prediction and Intelligent Troubleshooting in the Application of the Coin Cell Production Line, IJACT, Vol. 4, No. 6, p.149 ~ 156, (2012).

Google Scholar

[3] Yajie Yue, Chenming Sha, Xiaojing Zhang, Implementation of Serial Communication between Host Computer and PLC based on Host Link Protocol, IJACT, Vol. 4, No. 18, p.80 ~ 88, (2012).

DOI: 10.4156/ijact.vol4.issue18.10

Google Scholar

[4] Yun Niu, Lurong Cao, Xuguang Wu, ShouJun Song, Optimal Co-design of Control and Scheduling for Distributed Industrial, AISS, Vol. 4, No. 13, p.135 ~ 143, (2012).

Google Scholar

[5] Zhou Baiqing, The Building of Distributed Automation Control Systems based on PLC Programming and Extends IEC 61131 Standard, JDCTA, Vol. 6, No. 14, p.322 ~ 331, (2012).

DOI: 10.4156/jdcta.vol6.issue14.40

Google Scholar

[6] Li Jun, Kan Shulin, The Study on Multi-motor Control System Based on Fuzzy PID Control and BP Neural Network, AISS, Vol. 4, No. 1, p.100 ~ 107, (2012).

DOI: 10.4156/aiss.vol4.issue1.13

Google Scholar