Greenhouse air temperature control using the particle swarm optimization algorithm

This work presents a scheme for temperature control of a greenhouse located in the North of China. Since the treated greenhouse is a nonlinear system and subjects to strong external disturbances, a nonlinear model predicative control algorithm based on particle swarm optimization (PSO) is applied to solve the constrained nonlinear optimization problem. Its performance is compared with the ones obtained by using sequential quadratic programming (SQP) algorithm. PSO can get the global minimum quickly while SQP is going to be trapped in local minimum point. Simulations with the proposed method to design the model predictive temperature controller are presented and the result of it shows the effectiveness.