Particle Swarm Optimization (PSO) Model for Hydroponics pH Control System
Nutrients are essential to optimise plant growth. However, adding fertiliser changes the pH of the nutrition solution. This would impact plant growth as each plant types requires a specific pH range to thrive. Due to the nonlinearity characteristics, pH neutralisation adjustment is difficult but ess...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
UIKTEN
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/394040581aaa4a0ba0206e75f61b7604 |
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| Sumario: | Nutrients are essential to optimise plant growth. However, adding fertiliser changes the pH of the nutrition solution. This would impact plant growth as each plant types requires a specific pH range to thrive. Due to the nonlinearity characteristics, pH neutralisation adjustment is difficult but essential. In addition, alkaline solutions are not completely dissociated due to the presence of acid. For these reasons, a mathematical model to estimate the solution's pH would help improve the alkaline and acidic delivery accuracy. This study represents a pH water neutralisation behaviour using Particle Swarm Optimisation algorithm (PSO). The project begins with input and output data acquisition leading to the development of the PSO model. The model fit and residual distribution have also been analysed for this model. The model's performance was accepted based on a correlation test because the lag signal exceeded 95% of the confidence interval. The model also recorded a very minimal error, and this proved that a good agreement is established between the predicted and actual pH values. |
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