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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...
The Particle Swarm Optimization (PSO) algorithm is applied in this work to identify some parameters of a greenhouse model whose values are difficult to obtain. The model is described as functions of the outside climate and actuators actions without control. The parameters of the model are obtained applying PSO to minimize a proposed error function. The obtained model is validated using real data from...
In this paper, it is presented an optimal and intelligent technique to ventilate a greenhouse during the day. This technique is the result of the combination of a neural network and the particle swarm optimization algorithm. First, predictions on the dynamic behavior of the system variables are computed by means of a multilayer recurrent perceptron, trained with an extended Kalman filter. Then, using...
The voltage regulation is one of the main problems to be dealt in distributed generation photovoltaic systems. Loads and distributed generation production can be assumed as random variables. Results demonstrate that the suggested method can be applied for the maintaining of voltages within established limits at all load nodes of a photovoltaic grid-connected system (PVGCS). To assess the performance...
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