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《Journal of Tea Science》 2019-02
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Design and Experiment of the Temperature Control System of the Fuzzy RBF Neural Network PID in Tea Fixing Machine

PAN Yucheng;LIU Baoshun;HUANG Xianzhou;CHEN Xiaoli;LYU Xianyin;Department of Mechanical and Electronic Engineering, Ningde Vocational and Technical College;Wuyishan Manting Rock Tea Research Institute;Department of Biotechnology, Ningde Vocational and Technical College;Department of Information Techonlogy and Engineering, Ningde Vocational and Technical College;  
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.
【Fund】: 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)
【CateGory Index】: TS272.3
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Chinese Journal Full-text Database 10 Hits
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