【摘要】 针对温室非线性、时变性、延时性、多变量耦合等问题,对温度、湿度、光照强度和CO2浓度等环境因子进行分析,把模糊推理运用到温室环境控制系统,利用专家经验和知识行为转化为相应的模糊控制规则;结合神经网络控制理论,以温度和湿度作为主要控制变量设计模糊神经网络控制系统。仿真结果表明,该系统响应速度快,抗干扰能力强,对温室环境中温湿度有较好的控制效果,可为智能温室自动控制系统设计提供一定参考。更多还原

【Abstract】 For greenhouse nonlinear,time-varying,time delay and multivariable coupling problems,the temperature,humidity,light intensity and CO2 concentration and other environmental factors were analyzed,the fuzzy inference is applied to the control systems of greenhouse environment,then transforms expert experience and knowledge behavior into the corresponding fuzzy control rules;combined with theory of neural network control,and temperature and humidity as control variable fuzzy neural network control system is established.The simulation results show that the system response fast,strong anti-jamming capability,combined with theory of neural network control,it has a better control effect on the temperature and humidity in the greenhouse environment,and provide some reference for the design on intelligent greenhouse automatic control system.And provide a reference of intelligent greenhouse environment control system.更多还原