A Constrained MPC Approach Applied to Buck DC-DC Converter for Greenhouse Powered by Photovoltaic Source

The use of renewable energies in agricultural production systems gains a great interest in recent years, especially in greenhouses process. The objective of using renewable energies sources is to make the greenhouse system able to satisfy its energy needs. This paper proposes a new strategy based on Model Predictive Control to control battery charging and power greenhouse system from photovoltaic sources despite fluctuations due to its intermittent and uncertainties of converter parameters. This approach deals with optimization criterion problem in presence of constrained conditions. The constraints concern signal control applied to DC-DC converter, voltage and eventually current in desired proportions. Without loss of generality, Constrained Model Predictive Control is applied to a buck DC-DC converter to control the duty cycle of PWM switch. Simulation results shows effectiveness and robustness of the proposed approach to optimise battery charging and inverters for actuators powering.