基于BP神经网络PID控制器在水产温室温度控制中的应用
Application of PID Controller Based on BP Neural Network in Temperature Control of Aquaculture Greenhouse
于海南 1郑荣进 1步文月 1蒋欢1
作者信息
- 1. 浙江大学生物系统工程与食品科学学院,浙江杭州310029
- 折叠
摘要
针对水体大比热容性造成的水产温室水温变化非线性、大滞后性、时变性等问题,考虑到传统PID控制器自适应能力差、鲁棒性不强等缺陷,提出采用基于BP神经网络的PID控制策略.在该控制策略中,PID的控制参数可以通过神经网络进行实时调节,以实现最佳的控制效果.利用MATLAB软件对传统的PID控制策略和神经网络PID控制策略的控制效果进行仿真模拟.研究结果表明,基于BP神经网络PID控制的系统动态响应更快、鲁棒性更强、稳态精度更高、超调量更小,具有更好的控制效果.
Abstract
Aiming at non-linearity,large delay and time variant of aquaculture greenhouse due to high specific heat capacity of water,considering that the traditional PID controller has poor adaptive ability and robustness,a PID control strategy based on BP neural network was proposed.In this controller,the PID control parameter canbe tuned real-timely by neural network to achieve the best control effect.The traditional PID control strategy and PID control strategy based on BP neural network were simulated by using MATLAB.The results showed that the neural network based PID control strategy has quick dynamic response, small overshoot, strong robustness and better control effect.
关键词
水产温室/PID控制/神经网络Key words
Aquaculture greenhouse/PID control/Neural network引用本文复制引用
基金项目
浙江省重点科技创新团队资助项目(2011R50029)
出版年
2016
国家科技期刊平台
NSTL
维普
万方数据