王定成, 乔晓军, 汪春秀, 朱天一. 基于作物响应的温室环境SVMR控制仿真[J]. 农业工程学报, 2010, 26(14): 290-293.
    引用本文: 王定成, 乔晓军, 汪春秀, 朱天一. 基于作物响应的温室环境SVMR控制仿真[J]. 农业工程学报, 2010, 26(14): 290-293.
    Wang Dingcheng, Qiao Xiaojun, Wang Chunxiu, Zhu Tianyi. Simulation of greenhouse environment SVMR control based on plant response[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(14): 290-293.
    Citation: Wang Dingcheng, Qiao Xiaojun, Wang Chunxiu, Zhu Tianyi. Simulation of greenhouse environment SVMR control based on plant response[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(14): 290-293.

    基于作物响应的温室环境SVMR控制仿真

    Simulation of greenhouse environment SVMR control based on plant response

    • 摘要: 在温室环境控制中,传统的根据专家经验的设定值确定控制的目标,由于经验的局限性和作物生长的适应性等原因而不能准确确定设定值,影响温室生产的效率。该文采用仿真模型,研究根据作物响应自动确定控制目标的温室环境控制方法。根据作物生长模型和温室环境变化模型采用遗传算法自动确定温室环境的设定值,采用稳定性、鲁棒性好的OS-LSSVMR(在线稀疏最小二乘支持向量机回归)内模控制进行温室环境控制。通过仿真,在相同室外条件下,基于作物响应的温室环境控制方法消耗的能量更少,作物的干质量增加的更多,控制的精度更高。说明了该方法与传统的控制方法相比较,具有节能、稳定性好等特点,可以提高温室生产的经济效益。

       

      Abstract: In the greenhouse environment control, it is hard to gain the control object value correctly to take expert empirical set point as control object traditionally, because of the limitation of expert experience and the adaptability of crop growth, thus the greenhouse produce efficiency is affected. This paper presented a control method for the greenhouse environment, which can automatically set the environment control object according to the crop growth response by simulation. With this method the control objective value can be set automatically by model of greenhouse environment change and the crop growth using genetic algorithm, and OS-LSSVMR(online spare least square support vector machines regression) internal model control with good stability and robustness was adapted to carry on greenhouse environment control. The simulation results show that the method requires less energy, and more dry matter can be gained, It can gain more precision control compared with the traditional control method. Therefore, the method has the characteristics of energy saving and good stability, and can enhance the economic effectiveness of greenhouse production.

       

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