Simulation Experiment of Differential Improvement Based on PID Control Algorithm

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Abstract:

The network information processing is realized by the interaction between the processing units, differential forward PID control is the discrete control that is applied to PID control and traditional PID control, and they will produce an improved control method that is an improvement and optimization on the traditional PID control. Firstly, this paper carries on analysis for the conventional control system structure of industrial production process, while the conventional PID control algorithm has been specially compared. On the basis, the modified differential forward PID control is built, and to validate the stability of the system, using MATLAB special simulation tools carry out control effect of simulation experiment. The experimental results show that the improved system can obtain good control effect by weighted processing, to provide technical support for the research of this field to a certain extent.

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775-778

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February 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Long Xiaolin, Xu JinFang. Study on PID controller based on optimization BP neural network [J]. Computer measurement & control, 2003, 11 (2): 106-108.

Google Scholar

[2] Shen Yongfu, Wu Shaojun. Intelligent PID control [J]. Industrial instrumentation & automation, 2012(6): 11-13.

Google Scholar

[3] Liu Jinkun. Advanced PID control MATLAB simulation [M]. Beijing: Publishing House of electronics industry, 2011: 210-220.

Google Scholar

[4] Niu Jianjun, Wu Wei. Neural network self-tuning PID control strategy and simulation [J]. Journal of system simulation, 2012, 17 (6): 1425-1427.

Google Scholar

[5] Liu Jinkun. Advanced PID control MATLAB simulation (Second Edition) [M]. Beijing: Publishing House of electronics industry, 2011: 330-340.

Google Scholar

[6] Li Zhengzhou. MATLAB digital signal processing and its application [M]. Beijing: Tsinghua University press, 2011: 110-126.

Google Scholar

[7] Tang Xianlun. The application of PID algorithm in cascade control system based on MATLAB [J]. Journal of Chongqing University (NATURAL SCIENCE EDITION), 2011, 9(28): 61-63.

Google Scholar

[8] He Jiandong. The PID controller parameter tuning and simulation based on MATLAB [J]. Journal of Xi'an University of Science and Technology, 2011(4): 511-515.

Google Scholar

[9] Shun Tian. System analysis and design based on MATLAB-neural network [M]. Xi'an: Xi'an Electronic and Science University press, 2011: 23-40.

Google Scholar

[10] Nunzio Cappuccio, Diego Lubian. The fragility of the KPSS stationary test [J]. Statistical Methods and Applications, 2010 (2): 89-90.

Google Scholar

[11] Xiao Jian. Research and application of advanced control technology in active balancing system [D]. Beijing University of Chemical Technology, 2011: 1-9.

Google Scholar

[12] Sun Pingchun. The single loop control system PID parameter tuning [J]. Science and technology information, 2012(32): 47-48.

Google Scholar