Attitude Control for Optimal Generation of Energy From Multiple Energy Sources

This paper presents the design of algorithms and a low-cost experimental setup for a graduate course on hybrid control systems offered to non-electrical engineering majors. The purpose of the developed hands-on educational kit is two-fold. First, it aims at incorporating in the classroom a basic yet important problem emerging in generation of renewable energy of current global relevance: optimal extraction of solar and wind energy. Second, it introduces non-electrical engineering majors to issues of implementation of advanced control algorithms. The setup consists of a rotating base with an elevation arm to orient the attitude of modular energy collectors mounted at its tip. The base and arm are linked to a drive train that is powered by a small servo motor and provides the propulsion to orient the attitude of the setup. Solar and wind turbine modules can be attached to the arm. An Arduino microcontroller and associated sensors are used to control both the base and the arm. A Matlab/Simulink module has been created for this purpose. Students are able to design hybrid controllers to stabilize the attitude of the setup in order to maximize energy extraction. In this paper we present results on extraction of solar energy using solar tracking algorithms. The setup and algorithms have been tested in a hybrid control class offered to graduate students in aerospace and mechanical engineering.