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This paper presents the design and implementation of a model-based predictive controller (MPC) with the aim of reducing electrical energy consumption during the development of solar trajectory tracking tasks for a two-axis Solar Tracker. For the design of the MPC, it is necessary to know the specific parameters of each actuator of the Solar Tracker. Therefore, the design and implementation of an experimental methodology based on an algebraic approach to offline parameter identification is also presented. On the other hand, to validate the MPC proposal, an experimental methodology was carried out that allows evaluating and comparing its performance with that of two classical controllers. The above, in terms of tracking error and energy consumption. The results show that the MPC reduces on average 90% of the energy consumption, but it has a higher tracking error of approximately 0.5°. Therefore, based on this, analysis and discussion are provided. [Display omitted] • Integral MPC strategy that involves the system identification. • Energy consumption improvement with respect to classic controllers. • Numerical and experimental validations for the sake of reproducibility. • Comprehensive description of the theoretical and experimental developments. [ABSTRACT FROM AUTHOR]