ISHS Acta Horticulturae 534: International Conference and British-Israeli Workshop on Greenhouse Techniques towards the 3rd Millennium
A GREENHOUSE CLIMATE MULTIVARIABLE PREDICTIVE CONTROLLER |
| Authors: | J. Boaventura Cunha, C. Couto, A.E.B. Ruano |
| Keywords: | Agriculture, dynamic models, identification alogarithms, predictive control |
| Abstract:
A multivariable predictive controller was implemented to regulate the air temperature, humidity and CO2 concentration for a greenhouse located in the north of Portugal. The controller outputs are computed in order to optimise the future behaviour of the greenhouse environment, concerning the set-point accuracy and the minimisation of energy inputs. This is accomplished by using an optimisation module that minimises a cost function proportional to the sum of the squared errors between the simulated and desired outputs plus the square of the incremental and absolute energy inputs over a prediction horizon of one hour. Since the controller must be able to predict the greenhouse environmental conditions over the specified time interval, it is necessary to use mathematical models that describe the greenhouse climate, as well as to predict the outside weather. The experiments showed that second order ARX and tenth order ARMA models are well suited to simulate the inside and outside climate conditions, respectively. Since the model parameters are time-varying, recursive identification techniques were applied to estimate in real-time their values. The models employ data from the air temperature and humidity, inside and outside the greenhouse, solar radiation, wind speed and control inputs. To minimise the cost function a sequential quadratic programming method was used to solve the constrained optimisation problem. The results achieved with the proposed controller proved to be suitable for this application. Moreover, the controller performance, when compared to other control techniques such as commercially available PID controllers, was greatly improved. | |
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