神经网络PID控制器对植物工厂温度控制研究  

Study on temperature control of plant factory based on neural network PID controller

作　　者：崔世钢[1] 秦建华[1] 张永立[1] 

机构地区：[1]天津职业技术师范大学天津市信息传感与智能控制重点实验室,天津300222

出　　处：《天津职业技术师范大学学报》2017年第3期45-48,共4页Journal of Tianjin University of Technology and Education

基　　金：国家高技术研究发展计划项目(863计划)(2015AA033303)

摘　　要：植物工厂中的温度具有非线性、大滞后、大延迟及大惯性等特性,采用传统PID控制策略进行控制的效果不理想。针对这一问题,本文将BP神经网络智能算法和传统PID控制理论相融合,设计了基于BP神经网络自整定的PID控制器,同时给出相应算法并进行MATLAB仿真。仿真结果表明:与传统PID控制相比,设计的BP神经网络PID控制器对温度的控制具有更好的稳定性和鲁棒性,控制品质具有明显优势。In view of the characteristics of temperature, such as nonlinearity,large delay,large delay,large inertia and so on, when the traditional PID control strategy is adopted, the control effect is not ideal.Therefore, this paper combines the BP neural network intelligent algorithm with the traditional PID control theory, proposing the PID controller based on BP neural network self-tuning, and giving the corresponding algorithm and MATLAB simulation.The simulation results show that, com- pared with the traditional PID controller,the BP neural network PID controller designed in this paper has better stability and robustness to control the temperature in the plant factory and the control quality has obvious advantages.

关 键 词：植物工厂 温度 BP神经网路PID MATLAB仿真 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]