| 茶叶杀青机模糊RBF神经网络PID温控系统设计与试验 |
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| 引用本文： | 潘玉成,刘宝顺,黄先洲,陈小利,吕仙银.茶叶杀青机模糊RBF神经网络PID温控系统设计与试验[J].茶叶科学,2019,39(2):139-149. |
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| 作者姓名： | 潘玉成 刘宝顺 黄先洲 陈小利 吕仙银 |
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| 作者单位： | 宁德职业技术学院机电工程系,福建 福安,355000;武夷山市幔亭岩茶研究所,福建 武夷山,354300;宁德职业技术学院生物技术系,福建 福安,355000;宁德职业技术学院信息技术与工程系,福建 福安,355000 |
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| 基金项目： | 基于模糊神经网络的PID控制方法研究、福建省教育厅科技项目（JAT171132） |
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| 摘 要： | 针对滚筒式杀青机温控系统具有时变不确定非线性的特点,采用常规PID控制难于满足控制要求,利用模糊控制的良好收敛性和对模糊量的运算优势,以及神经网络自学习、自适应的特性,将常规PID控制与模糊控制、神经网络结合起来,提出一种基于模糊RBF神经网络的PID控制策略,实现了对PID参数的实时在线整定。MATLAB软件仿真与试验结果表明,模糊RBF神经网络PID控制与常规PID控制相比,系统具有更好的动静态特性和抗干扰性能,温度控制误差在±2℃范围内,能很好地满足茶叶杀青工艺对温度的控制要求,保证了茶叶的杀青质量。
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| 关 键 词： | 茶叶杀青机 杀青温度 模糊RBF 神经网络 PID控制 MATLAB仿真 |
| 收稿时间： | 2018-06-14 |
Design and Experiment of the Temperature Control System of the Fuzzy RBF Neural Network PID in Tea Fixing Machine |
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| 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. |
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| Authors: | PAN Yucheng LIU Baoshun HUANG Xianzhou CHEN Xiaoli LYU Xianyin |
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| Institution: | 1. Department of Mechanical and Electronic Engineering, Ningde Vocational and Technical College, Fu′an 355000, China; 2. Wuyishan Manting Rock Tea Research Institute, Wuyishan 354300, China; 3. Department of Biotechnology, Ningde Vocational and Technical College, Fu′an 355000, China; 4. Department of Information Techonlogy and Engineering, Ningde Vocational and Technical College, Fu′an 355000, China; |
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| 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. |
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| Keywords: | tea fixing machine temperature of fixation fuzzy RBF neural network PID control MATLAB simulation |
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