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作 者:应文渊 赵章风[1] 钟江[1] YING Wen-yuan;ZHAO Zhang-feng;ZHONG Jiang(College of Mechanical Engineering,Zhejiang University of Technology,Hangzhou 310014,China)
机构地区:[1]浙江工业大学机械工程学院,浙江杭州310014
出 处:《机电工程》2018年第12期1342-1347,1360,共7页Journal of Mechanical & Electrical Engineering
基 金:国家自然科学基金资助项目(31201138);浙江省科技厅重点研发项目(2017C02027)
摘 要:针对滚筒杀青机控制依赖人工经验,且传统PID算法控制精度不高导致坏叶产生这一问题,根据对滚筒杀青机的设备结构与杀青流程、模糊算法、BP神经网络PID控制算法的研究,提出了基于STM32 ARM Cortex-M3内核单片机的、将模糊推理与BP神经网络PID自整定技术结合的滚筒杀青机改进控制算法。基于该算法的闭环控制系统,以茶叶含水率与设备投叶速度作为输入,以模糊算法决策对应滚筒温度,以BP神经PID自整定算法实现了温度控制,最后利用Matlab对系统各部分进行了仿真和建模,进行了杀青效果的对比实验。研究结果表明:BP神经网络PID控制应用于茶叶杀青控制系统,其系统阶跃响应的调节时间比常规PID控制算法要短、超调量更小、控制更精确,改进算法后的控制系统的茶叶杀青质量更好。Aiming at the existence of bad leaves caused by the roller tea-fixing machine's dependence on human-experience,and the low control accuracy of traditional PID algorithm,fuzzy algorithm and BP neural network PID self-tuning technology were combined for improving control algorithm of the machine,based on the structure and process of the fixing machine,fuzzy algorithm,BP neural network PID control algorithm and STM32ARM Cortex-M3core single-chip microcomputer.In the closed-loop control system based on that algorithm,tea leaves'moisture content and leaf-transport speed were taken as inputs,fuzzy algorithm was used to decide the corresponding roller temperature, and then BP neural network PID self-tuning algorithm was used to achieve temperature control.Finally,Matlab was used to simulate'and model the various parts of the system,and to compare the effect of fixation to verify the effect.The research results indicate that while the BP neural network PID control is applied to the tea-fixing control system,the adjustment time of the system step response is shorter than the conventional PID control algorithm,the overshoot is smaller,the control is more accurate.At the same time,the improved control system has a better performance in the quality of tea-fixing.
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