茶叶杀青机模糊RBF神经网络PID温控系统设计与试验

doi:10.13305/j.cnki.jts.2019.02.003

Abstract

Abstract: Due to the characteristics of time-varying uncertainty and nonlinearity of the temperature control system of rotary fixing machine, the conventional PID control parameters are difficult to meet the control requirements. Based on the good convergence of fuzzy control, computing advantages of fuzzy quantity and the self-learning and -adapting characteristics of neural network, a PID control strategy combined PID control, fuzzy control and neural network was proposed to achieve real-time online tuning of PID parameters. The simulation and test results of MATLAB software show that the fuzzy-RBF neural network PID control had better dynamic and static characteristics and anti-jamming performance than the conventional PID control. The temperature control error was within ±2℃, which well met the temperature control requirements of the tea fixation process and ensured the quality.

Key words: tea fixing machine, temperature of fixation, fuzzy RBF neural network, PID control, MATLAB simulation

CLC Number:

TS272.3

PAN Yucheng, LIU Baoshun, HUANG Xianzhou, CHEN Xiaoli, LYU Xianyin. Design and Experiment of the Temperature Control System of the Fuzzy RBF Neural Network PID in Tea Fixing Machine[J]. Journal of Tea Science, 2019, 39(2): 139-149.

References

[1] 袁英芳. 绿茶杀青技术研究概述[J]. 茶叶通讯, 2010, 37(1): 37-39, 43.
[2] 赵梨铭. 茶叶智能化汽热杀青机控制系统[J]. 轻工机械, 2009, 27(2): 71-73.
[3] 彭秀英, 陈亚, 罗艳蕾. 基于PLC控制的电加热滚筒杀青机温度控制系统[J]. 农机化研究, 2011(4): 186-189.
[4] 林启军. 基于模糊技术的滚筒式茶叶杀青机温度控制[D]. 长沙: 中南大学, 2011: 18-29.
[5] 沈斌. 茶叶杀青系统自动控制技术研究[D]. 杭州: 浙江工业大学, 2013: 33-39.
[6] 毛晓文. 基于模糊PID控制和在线检测技术的绿茶杀青自动控制系统的研究与应用[D]. 合肥: 安徽农业大学, 2014: 20-26.
[7] 徐海卫, 蒋丽, 程宇菥, 等. 茶叶杀青温度精准控制系统研究[J]. 中国测试, 2015(11): 64-67, 72.
[8] 曹成茂, 吴正敏, 梁闪闪, 等. 茶叶杀青机双模糊控制系统设计与试验[J]. 农业机械学报, 2016, 47(7): 259-265.
[9] 陈雯柏. 人工神经网络原理与实践[M]. 西安: 西安电子科技大学出版社, 2016: 140-147.
[10] 何晶, 张宪, 赵章风, 等. 基于PFC3D的茶叶杀青过程数值模拟和设备参数分析[J]. 茶叶, 2013, 39(1): 17-23.
[11] 宋志禹. 节能型自动化控制茶叶滚筒杀青机的研究[D]. 合肥: 安徽农业大学, 2010: 12-16.
[12] 郭凯, 郭奇, 李大伟, 等. 模糊神经网络PID控制器设计及在常减压装置中的应用[J]. 自动化应用, 2016(2): 14-15, 18.
[13] 胥良, 郭林, 梁亚, 等. 基于模糊RBF神经网络的智能PID控制[J]. 工业仪表与自动化装置, 2015(6): 67-69, 75.
[14] 戴赛. 基于模糊RBF神经网络的磁悬浮系统研究[D]. 哈尔滨: 哈尔滨理工大学, 2012: 22-25.
[15] 王晓远, 傅涛. 基于模糊RBF神经网络的无刷直流电机控制[J]. 微电机, 2015, 48(11): 33-36, 88.
[16] 范春丽. 基于模糊神经网络的智能优化PID控制器研究[D]. 北京: 北京化工大学, 2009: 25-29.
[17] 付光杰, 张微微, 牟海维. 基于模糊RBF网络高频感应加热电源控制的研究[J]. 化工自动化及仪表, 2014, 41(4): 357-361, 376.
[18] 李燕强. 模糊RBF神经网络在人脸识别的应用研究[D]. 广州: 广州大学, 2011: 44-47.
[19] 郝朝会, 孙传祝, 苏夏侃. 自适应模糊PID控制在茶叶杀青机中的应用[J]. 农机化研究, 2013(2): 201-204.
[20] 刘金琨. 先进PID控制MATLAB仿真[M]. 4版. 北京: 电子工业出版社, 2016: 311-323.
[21] 王华强, 石亚娟, 王健波. 神经网络模糊PID在水轮机调速系统中的应用[J]. 合肥工业大学学报(自然科学版), 2012, 35(9): 1187-1191.
[22] 潘玉成, 林高飞, 陈小利, 等. 基于模糊专家控制的茶叶炒制温度控制系统[J]. 食品与机械, 2016, 32(11): 79-84.
[23] 李梦瑶. 基于模糊神经网络PID算法的电阻炉温度控制系统的研究[D]. 焦作: 河南理工大学, 2014: 55-61.

Design and Experiment of the Temperature Control System of the Fuzzy RBF Neural Network PID in Tea Fixing Machine

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 3

Metrics

Comments

Recommended 10

[1]	ZHAO Runmao, BIAN Xianbing, CHEN Jianneng, DONG Chunwang, WU Chuanyu, JIA Jiangming, MAO Ming, XIONG Yongsen. Development and Test for Distributed Control Prototype of the Riding Profiling Tea Harvester [J]. Journal of Tea Science, 2022, 42(2): 263-276.
[2]	LI Bing, SUN Changying, LI Weining, SONG Yangyang. Design and Experiment of Tea Far Infrared Dryer Based on DMC-PID Cascade Control [J]. Journal of Tea Science, 2018, 38(4): 410-415.
[3]	WEI Shiqin, JIN Xinyi, HUANG Jiachun, HAO Zhilong, OUYANG Jingsheng, LIN Jie. The Temperature PID Control System of Dryer and Its Application on Dahongpao Baking [J]. Journal of Tea Science, 2014, 34(6): 557-564.