面向燃气调压应用的RBF人工智能控制策略

计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 138-141.

面向燃气调压应用的RBF人工智能控制策略

何进¹, 仲元昌², 孙利利², 张晓帆²

重庆工程职业技术学院电气工程学院重庆402260¹;
重庆大学微电子与通信工程学院重庆400044²

出版日期:2019-06-14 发布日期:2019-07-02
通讯作者: 仲元昌(1965-),男,博士,教授,主要研究方向为通信与测控系统、多目标跟踪等,E-mail:zyc@cqu.edu.cn
作者简介:何进(1976-),男,硕士,副教授,主要研究方向为计算机信息技术等;孙利利(1996-),硕士生,主要研究方向为通信与测控系统;张晓帆(1993-),硕士生,主要研究方向为通信与测控系统。
基金资助:
本文受国家“973”项目(2012CB215202),中央高校基本科研业务费专项项目(106112018CDPTCG000／41,106112017CDJZRPY0101),重庆市科技创新专项(cstc2017shmsA40003),重庆市教委科研项目(KJ1603206)资助。

RBF Artificial Intelligence Control Strategy for Gas Pressure Regulating Application

HE Jin¹, ZHONG Yuan-chang², SUN Li-li², ZHANG Xiao-fan²

Chongqing Vocational Institute of Engineering,Chongqing 402260,China¹;
School of Microelectronics and Communication Engineering,Chongqing University,Chongqing 400044,China²

Online:2019-06-14 Published:2019-07-02

摘要/Abstract

摘要： 针对现有中低压调压站调压精度差、可靠性差的不足,提出一种面向燃气调压器应用的RBF神经网络控制策略。其智能燃气调压器利用高阶系统的降阶近似处理方法,得到简化的电动燃气调压系统数学模型;然后,针对调压系统的非线性、不确定性特征,充分利用RBF神经网络对非线性函数良好的逼近效果,实现PID参数自整定。通过基于MSP430单片机开发板对调压器的算法性能及功能进行测试,测试结果表明,相比于传统PID控制算法,改进的算法的调节时间缩短约10%,超调量减少约6%,且抗干扰性能优越,调压器能实现数据采集、调压、串口通信、安全报警功能。

关键词: MSP430, PID控制, 神经网络, 智能燃气调压器

Abstract: In order to overcome the shortcomings of poor accuracy and reliability of the existing medium and low voltage regulator stations,a RBF neural network control strategy for gas regulator application was proposed.The intelligent gas regulator uses the reduced order approximation method of high-order system to obtain a simplified mathematical model of electric gas regulator system.Then,according to the characteristics of non-linearity and uncertainty of the regulator system,it makes full use of the good approximation effect of RBF neural network for the non-linear function to realize the self-tuning of PID parameters.The performance and function of the voltage regulator are tested based on MSP430 MCU development board.The test results show that compared with the traditional PID control algorithm,the improved algorithm reduces the adjustment time by about 10% and the overshoot by about 6%,and the anti-interference performance is superior.The voltage regulator can realize data acquisition,voltage regulation,serial communication and safety alarm functions.

Key words: Intelligent gas regulator, MSP430, Neural network, PID control

中图分类号:

TP181

何进, 仲元昌, 孙利利, 张晓帆. 面向燃气调压应用的RBF人工智能控制策略[J]. 计算机科学, 2019, 46(6A): 138-141. https://doi.org/

HE Jin, ZHONG Yuan-chang, SUN Li-li, ZHANG Xiao-fan. RBF Artificial Intelligence Control Strategy for Gas Pressure Regulating Application[J]. Computer Science, 2019, 46(6A): 138-141. https://doi.org/

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