Development and research of intelligent PID controller based on fuzzy neural network

被引：0

作者：

Qiuhua, Xu ^{[1
]}

机构：

[1] Zhoukou Vocational College of Science and Technology, China

来源：

Open Automation and Control Systems Journal | 2014年 / 6卷 / 01期

关键词：

Fuzzy control; Matlab software; Neural network; NNbox toolbox; PID controller;

D O I：

10.2174/1874444301406011474

中图分类号：

学科分类号：

摘要：

In this paper, intelligent fuzzy control theory is introduced in the model of neural network algorithm, and the neural network system is improved by the PID controller, which has realized the feedback and adjustment function of neural network system, and has made the reaction of the system be more accurate and stable. In order to verify the validity and reliability of the designed intelligent control PID algorithm based on the fuzzy neural network in this paper, the algorithm is carried on the programming by using Matlab programming software, and the control process of PID is calculated by NNbox simulation toolbox, at last, it has obtained the curve of PID control response changing over time. From the response curve, it can be seen that after the PID proportional coefficient is regulated by using fuzzy neural network intelligent control algorithm, it can quickly and steadily obtain the control curve, which has realized better intelligent control effect, and has provided technical reference for the research of intelligent PID controller. © Xu Qiuhua; Licensee Bentham Open.

引用

页码：1474 / 1479

页数：5

共 14 条

[1]

Dan X., Wang G., Cao B., Feng X., Study on optimization torque distribution strategy for independent 4WD electric vehicle, Journal of Xi'an Jiao Tong University, 46, 3, pp. 1-5, (2012)

[2]

Li G., Yi L., He H., Regenerative braking control strategy for electric vehicle, Transactions of Beijing Institute of Technology, 29, 6, pp. 520-524, (2009)

[3]

Zhao Y., Fen Lin. Vehicle state estimation based on UKF algorithm, China mechanical engineering, 21, 5, (2010)

[4]

Ding H., Guo K., Li F., Et al., Arbitrary path and speed following driver model based on vehicle acceleration feedback, Journal of Mechanical Engineering, 5, 10, pp. 116-120, (2010)

[5]

Zong C., Liu J., Zheng H., Et al., Modeling and special condition simulation of electric vehicle with 4WID/4WIS, Automotive Engineering, 33, 10, pp. 829-833, (2011)

[6]

Zhou L., Luo Y., Et al., Braking control of electric vehicles while coordinating regenerative and anti-lock brakes, Journal of Tsinghua University, 5, 49, pp. 728-732, (2009)

[7]

Li J., Chen H., Li Y., Application of neural network decoupling control in central air-conditioning system, Journal of Shenyang Jianzhu University, 28, 1, pp. 182-186, (2012)

[8]

Li H., Yang J., An approach of cooling coils modeling based on two parameters, Building Energy &Amp

[9]

Environment, 28, 6, pp. 15-17, (2009)

[10]

Meng Q., Discussion of optimum energy-saving of water source heat pump with variable flow water system, Refrigeration and Air-Conditioning, 10, 1, pp. 84-89, (2010)

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