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出 处:《农机化研究》2009年第10期187-189,共3页Journal of Agricultural Mechanization Research
摘 要:为了实现温室节能以及安全控制,针对温室环境的大滞后、多输入、多输出、非线性和难以建立数学模型等特点,提出用模糊神经网络进行温室温度控制的方法,采用神经网络在线调整训练模糊规则的控制方式,实现了温室内温度的模糊控制。利用该方法能提高温室控制系统的精确性、适应性和鲁棒性,有利于节能。结果表明,基于模糊神经网络的温室控制系统运行效果良好,控制过程响应快,无震荡,超调量小,稳态误差小,能满足使用要求。In order to achieve energy-saving greenhouse,as well as safe control,in accordance for greenhouse control system,have behind a large,multiple-input,multiple-output,non-linear,it is difficult to establish mathematical models,and the temperature Control based on fuzzy neural-network of greenhouse been proposed,Use neural-network on-line training to adjust the rules of fuzzy control method to achieve a greenhouse temperature of fuzzy control.Use this method to improve the accuracy of the greenhouse control system,adaptive and robust,energy-saving benefit.The results show that the system is running well,the control process have rapid response,without shocks,small overshoot and steady-state error,can be used to meet the requirements.
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