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面向燃气调压应用的RBF人工智能控制策略 预览

RBF Artificial Intelligence Control Strategy for Gas Pressure Regulating Application
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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。 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.
作者 何进 仲元昌 孙利利 张晓帆 HE Jin;ZHONG Yuan-chang;SUN Li-li;ZHANG Xiao-fan(Chongqing Vocational Institute of Engineering,Chongqing 402260,China;School of Microelectronics and Communication Engineering,Chongqing University,Chongqing 400044,China)
出处 《计算机科学》 CSCD 北大核心 2019年第B06期138-141,共4页 Computer Science
基金 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。
关键词 智能燃气调压器 神经网络 PID控制 MSP430 Intelligent gas regulator Neural network PID control MSP430
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;通信作者: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;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。
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  • 1朱仲邃.变速积分PID算法在温度控制中的应用[J].仪器仪表用户,2005,12(3):68-68. 被引量:2
  • 2肖曙,谢沅清.PWM控制器SG3525的两种宏模型[J].北京邮电大学学报,1996,19(3):65-71. 被引量:4
  • 3伍筱菁.基于LabWindows/CVI和Matlab平台的温度控制系统设计与实现[J].传感技术学报,2006,19(1):187-190. 被引量:5
  • 4施金良 贾碧.微机控制的热丝法物质熔点测定仪.检测与仪表,1998,3:36-38. 被引量:3
  • 5Manjunath T C. Implementation of a Microcontroller Based Tem- perature Scanning Control System [ C ]//Proceedings of the SICE Annual Conference, 2005, 2761-2766. 被引量:1
  • 6Hirasawa, Shigeki ; Toda, et al. Precise Control Method of Temperature Rising Speed During Rapid Thermal Processing with Lamp Eeaters. Japan Society of Mechanical Engineers, 2008, 74 (4) : 767-773. 被引量:1
  • 7Moon U C, Lee K Y. Temperature Control of Glass Melting Furnace with Fuzzy Logic and Conventional PI Control[ C ]//Proceedings of the American Control Conference. Chicago, Illinois, 2000: 2720 -2724. 被引量:1
  • 8LI PENG, LIU GUANG-JUN, ZHANG YING-CHUN. Coiling Temperature Control of Hot Steel Strip Using Combined Feed Forward, Feedback and Adaptive Algorithms[ C ]//Institute of Electrical and Electronics Engineers Inc. , 2005 IEEE International Conference on Control Applications 2005. 被引量:1
  • 9Bojkovski J, Dmovsek J, Pusnik I, et al. Automation of a Precision Temperature Calibration Laboratory. IEEE Transactions on Instrumentation and Measurement, 2000, 49 ( 3 ) : 596-601. 被引量:1
  • 10HAN Pu, YU Ping, Wang Guoyu, et al. Predictive Functional Control in Thermal Power Unit Load Systems[ J]. Transactions of China Electrol Technical Society, 2004, 19(10) : 47 -52. 被引量:1

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