Our objectives are:
- Further our understanding of the physiological behaviour of roses, characterise the response of roses, examine flower quality, study the relationship between physiological flows in roses and environmental conditions (climate, substrate).
- Design and develop an automated climate control and fertilisation system adapted to the response of roses in a Mediterranean climate.
- Develop an ‘expert’ knowledge base for use in decision support for the management of rose crops.
- Integrate an on-site validation of prototypes for commercial rose farms.
The control algorithm must take into account the variables involved in calculating control actions. For proper control, it is necessary to have a dynamic model that includes all the bioclimatic phenomena involved in the process. Once the model is developed, the control algorithm must be considered: the first level of control consists of various local controls with basic PID controllers, and higher levels must then be added. These higher levels consist of a model-based predictive control that takes into account interactions between variables and default values for local controls.