Author:
Agyeman Bernard T.,Liu Jinfeng,Shah Sirish L.
Reference11 articles.
1. WWAP (United Nations World Water Assessment Programme)/UN-Water. (2018). The United Nations World Water Development Report 2018: Nature-Based Solutions for Water.
2. McCarthy, A. C., Hancock, N. H., Raine, S. R. (2014). Simulation of irrigation control strategies for cotton using Model Predictive Control within the VARIwise simulation framework. Computers and Electronics in Agriculture, 101:135–147.
3. Aske, E. M. B., Strand, S., & Skogestad, S.(2008). Coordinator MPC for maximizing plant throughput. Computers & Chemical Engineering, 32(1-2):195–204.
4. Delgoda, D., Malano, H., Saleem, S.K., & Halgamuge, M.N. (2016). Irrigation control based on model predictive control (MPC): Formulation of theory and validation using weather forecast data and AQUACROP model. Environmental Modelling & Software, 78:40–53.
5. Agyeman, B. T., Nouri, M., Appels, W., Liu, J., & Shah, S. L.(2024). Learning-based multi-agent MPC for irrigation scheduling Control Engineering Practice, 147:105908.