Predictive control algorithm using laguerre functions for greenhouse temperature control

Abstract

In this paper, a discrete time predictive control (DMPC) algorithm using Laguerre orthonormal functions based model was proposed for controlling the temperature under the greenhouse system. In order to design the controller, a state-space model of the temperature of the system is identified. The observer can be designed using concepts of Kalman filtering, which consider stochastic disturbance in the process and/or measurements. The efficiency of the DMPC method is established, due to a particular choice of the synthesis parameters (the horizon of prediction, the number of Laguerre functions and its scaling factor and the weighting matrices). The proposed algorithm was applied to a scenario consisting of temperature set-point changes. The system response performances of temperature stabilization were acceptable; through a real-time implementation to confirm the capacity of the developed technique for controlling the greenhouse temperature.