Modeling of a greenhouse prototype using PSO algorithm based on a LabViewTM application

This paper presents a simple method based on Particle Swarm Optimization (PSO) to identify several parameters in a proposed mathematical model of a greenhouse prototype. These parameters are sought in order to approximate the real characteristics of a greenhouse physic prototype building in CINVESTAV Unidad Guadalajara, by using the PSO to minimize a proposed error function, based on the estimation of the two more representative dynamics of the climate conditions inside the greenhouse: the air temperature and relative humidity. The implementation is carried out in an offline optimization schedule using real data recorded through the LabView^TM SignalExpress application, and a real-time implementation in a LabView^TM code to optimize the model in a sample-to-sample execution of the PSO. Validation shows a good agreement in a direct comparison with the real dynamic behavior of temperature and relative humidity measures inside the greenhouse prototype, as shown by the reached level of adaptation of the model through the several PSO tests under the best calibration conditions.