Abstract
For the simplest case with a single point measurement and a single heater under operational constraint on heater, a model predictive control [1] was already proposed and applied to evaluate in a real field test. The obtained results indicated the effectiveness of the control although searching for an optimal solution was essentially based on the brute-force attack. It is not feasible to extend the same approach to determine an optimal solution in the case of multipoint temperature measurements and multipoint heaters for calculations in a real time operation. For his problem, a genetic algorithm was applied as a solution to regulate greenhouse temperature for the above-mentioned problem. Model predictive control performance strongly depended on the precision of the mathematical model of greenhouse temperature dynamics, and thus, a recursive least square identification strategy was also introduced to update parameters in the predictor on line. The control results in a laboratory demonstration greenhouse indicated that the proposed method performed well and showed an average decrease of 20-35% in the temperature error. Furthermore, the temperature difference also decreased by an average of 36%.
Original language | English |
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Title of host publication | 2017 25th Mediterranean Conference on Control and Automation, MED 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 54-59 |
Number of pages | 6 |
ISBN (Electronic) | 9781509045334 |
DOIs | |
Publication status | Published - 2017 Jul 18 |
Event | 25th Mediterranean Conference on Control and Automation, MED 2017 - Valletta, Malta Duration: 2017 Jul 3 → 2017 Jul 6 |
Other
Other | 25th Mediterranean Conference on Control and Automation, MED 2017 |
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Country/Territory | Malta |
City | Valletta |
Period | 17/7/3 → 17/7/6 |
ASJC Scopus subject areas
- Control and Optimization
- Modelling and Simulation