Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10249962 | Computers and Electronics in Agriculture | 2005 | 15 Pages |
Abstract
These models have time variant parameters and so, recursive identification techniques are applied to estimate their values in real-time. The models employ data from the climate inside and outside the greenhouse, as well as from the control inputs. Simulations with the proposed methodology to design the model-based predictive air temperature controller are presented. The results indicate a better efficiency of the particle swarm optimisation algorithm as compared with the efficiencies obtained with a genetic algorithm and a sequential quadratic programming method.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
J.P. Coelho, P.B. de Moura Oliveira, J. Boaventura Cunha,