摘要
依据能量平衡的温室温度数字模型和实际温室的具体参数建立温室环境Matlab仿真模型,经温度预测误差统计分析,预测数据与真实数据的相关系数为0.968 877 07,决定系数为0.938 722 78。提出一种基于模糊专家控制与PID控制相结合的混合算法,该算法根据每个时间片实际温度与设定温度之间温度偏差与设定阈值比较选择不同控制算法。当温度偏差大于阈值时,选择模糊专家控制;小于阈值时,切换到PID控制,兼顾动态和稳态特性。仿真实验表明,提出的算法比优化前的开关控制、PID控制算法、专家模糊控制算法分别节能13.68%,9.07%,5.89%。实际应用证明,使用该算法控制的增温温室比传统开关控制的增温温室内种植的越冬番茄增产2.1%。
A Matlab simulation model for the greenhouse environment is created according to the energy-balanced greenhouse temperature digital model and the specific parameters of the actual greenhouse. The correlation coefficient （0.96887707） of predicted data and actual data, and the key coefficient （0.93872278） were obtained according to the results of analysis on the temperature forecast and the error statistics. A hybrid algorithm combining the fuzzy expert control with PID control is proposed. The algorithm can choose different control algorithms according to the comparison result between the deviation between the actual temperature and set temperature, and the specified threshold on each time slice. If the temperature deviation is greater than the threshold value, the fuzzy expert control is selected; if the threshold is less than the threshold value, the control mode is switched to the PID control. The algorithm gives consideration to both dynamic and steady states. The simulation results show that the proposed algorithm can save energy by 13.68% compared with the non-optimized switch control, save energy by 9.07% compared with the PID control algorithm, and save energy by 5.89% compared with the expert fuzzy control algorithm. The practical application shows that the temperature increasing system controlled by the algorithm can increase the yield of the winter tomato by 2.1%, compared with the traditional switch control system in the greenhouse.
出处
《现代电子技术》
北大核心
2017年第8期14-18,共5页
Modern Electronics Technique
基金
国家自然科学基金(61271207
61372104)
徐州市科技发展基金(XF13C035)
院级科研课题基金(XGY201414)
关键词
混合控制
模糊专家控制
PID控制
高效节能
温室
hybrid control
fuzzy expert control
PID control
efficient energy saving
greenhouse
