Optimal control of fruit-storage process using an intelligent control technique

本研究以提高果实贮藏品质为目标，采用模糊逻辑、神经网络和遗传算法对果实贮藏过程进行识别和优化控制。1）利用传感器研究了果实在贮藏过程中对环境因子（温度和相对湿度）的响应（失水和果皮颜色）。它们随环境变化的阶跃输入而动态变化。皮肤水分损失与环境之间呈线性关系，而皮肤颜色与环境之间呈强非线性关系。2）三层神经网络对水分损失等线性系统和皮肤颜色（成熟度）等非线性系统的识别都是有效的。另一方面，遗传算法被证明是非常有效的找到io 关于我们 3）提出了一种新的模糊控制技术，该技术利用神经网络和遗传算法有效地选择最优隶属函数和控制规则，并将其应用于水果贮藏室相对湿度的控制。控制输入是通气的开-关。控制目标是通过模糊控制实现通风的通断控制，使仓库内的相对湿度保持在理想值。结果表明，该控制方法能够成功地确定最优隶属函数和控制规则，其控制性能优于常规控制方法的上级。4）最后，基于番茄表面颜色，采用神经网络和遗传算法相结合的智能控制技术，研究了番茄贮藏过程中热处理的优化模式。得到了两种最佳热处理工艺。一种是单一的应用程序的热量，这是类似于传统的类型，另一个是间歇性的应用程序，定期给予。最后，将这两种优化处理方法应用于实际系统。结果表明，两种方法的成熟效果均优于连续冷却。少

In this study, new techniques for indentification and optimal controle of fruit-storage process using fuzzy logic, neural networks and genetic algorithms were developed, aiming at the qualitative improvement of fruit during storage.1) Fruit responses (water loss and skin color), as affected by environmental factors (temperature and relative humidity), during stroage were investigated using sensors. They showed dynamic changes against the step inputs of the environmental changes. The relationship between the water loss and the environment is characterized by linear while the relationship between the skin color and the environment is give by strong nonlinearity. So, it is found that they should be treated as dynamic and nonlinear systems.2) A three-layr neural network was effective for both indentification of the linear system such as a water loss and the nonlinear system such as a skin color (ripening). On the other hand, genetic algorithms were shown to be very effective to find the io … More ta-steps of optimal setpoints on temperature and relative humidity through simulation of the identified neural-network model.3) A new fuzzy control technique, which efficiently selects optimal membership functions and control rules by using neural networks and genetic algorithms, was developed and then applied to the control of relative humidity in a fruit-storage house. The control input is the on-off of ventilation. The control aim is to maintain the relative humidity in the storage house at the desired value through the on-off control of ventilation by the fuzzy control. Results show that this control technique allowed optimal membership functions and control rules to be successfully determined and its control performance was superior to the conventional control.4) Finally, an optimal pattern of heat treatment for tomatoes during storage was investigated based on their surface color, using an intelligent control technique consisting of neural networks and genetic algorithms. Two types of optimal heat treatments were obtained. One was the single application of heat, which is similar to the conventional type, and the other was intermittent application, given periodically. Finally, the two optimal treatments were applied to an actual system. The result showed that they gave better results on ripening than continuous cooling. Less