| heal.abstract |
An innovative se nsing method has been developed to replace leaf sensors in plant propagation systems and to provide better performance. The method in principle combines ordinary measurements, of ambient temperature, humidity and radiation, to calculate the control parameters of the humidification process in mist or fog propagation chambers. The new method is based on the fact that conditions of the microclimate are fully determined by the surrounding space, and implicitly relates the transfer phenomena between the two spaces through the setting of control parameters. The sum of products of the parameters with the measured macroclimatic variables provides an estimate of the moisture loss and determines the rate at which humidity should be supplied in the propagation chamber. An adaptive system, developed with a direct programming approach, guides the selection of control parameters to yield optimal system performance. The system is performance driven, conducts real experiments on the site and uses a modified descent method to maximise performance. The optimiser, after learning the best parameters values, updates a dictionary of parameters appropriate for each situation, which is recalled when conditions reoccur. Alternative performance functions are investigated taking into account the requirements of the physiological process of rooting and their implications regarding the microenvironment. The method is applicable to any system whose performance depends on a number of adjustable parameters. A mathematical model of the process is not necessary, as the learning system can be used whenever the performance can be measured by simulation or experiment. |
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