Design and implementation of analog controllers for a solar tracker

At present, a reasonable use of energy represents a fundamental aspect. Therefore it is important to develop devices and equipment that facilitates the accomplishment of this goal. This paper shows the design and implementation of different drivers for a solar tracking system. This solar tracker is designed to take measurements of solar energy harvesting. In this paper we describe and explain various devices, namely an onoff controller, a proportional controller and a compensator, which has a pole-zero and gain that can be optimized using genetic algorithms and particle swarms.

[1]  Mauro Birattari,et al.  On the Invariance of Ant Colony Optimization , 2007, IEEE Transactions on Evolutionary Computation.

[2]  T. Tudorache,et al.  A simple neural network solar tracker for optimizing conversion efficiency in off-grid solar generators , 2008 .

[3]  Katsuhiko Ogata,et al.  Ingeniería de control moderna , 1980 .

[4]  Butler Hine,et al.  BEES: exploring Mars with bioinspired technologies , 2004, Computer.

[5]  Orlando Arrieta Orozco,et al.  Sintonización de controladores PI y PID utilizando los criterios integrales iae e itae , 2011 .

[6]  Angus R. Simpson,et al.  Parametric study for an ant algorithm applied to water distribution system optimization , 2005, IEEE Transactions on Evolutionary Computation.

[7]  Thomas Stützle,et al.  Ant colony optimization: artificial ants as a computational intelligence technique , 2006 .

[8]  Chi-Tsong Chen,et al.  Analog and Digital Control System Design: Transfer-Function, State-Space, and Algebraic Methods , 1993 .

[9]  Thomas Weise,et al.  Global Optimization Algorithms -- Theory and Application , 2009 .

[10]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[11]  T. C. Kuo,et al.  Solar Tracking Fuzzy Control System Design using FPGA , 2009 .

[12]  Samuel Lakeou,et al.  Design Of A Low Cost Solar Tracking Photo Voltaic (Pv) Module And Wind Turbine Combination System. , 2006 .

[13]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[14]  Leopoldo Vega Franco,et al.  Sinopsis de pruebas estadísticas no paramétricas. Cuándo usarlas , 2003 .