为了实现智能灌的建模,优化和预测控制框架
Erion Bwambale1,2, Felix K Abagale2,3, Geophrey K Anornu4
1Department of Agricultural and Biosystems Engineering, Makerere University, P. O. Box 7062, Kampala, Uganda.
Heliyon
|October 4, 2024
概括
模型预测控制 (MPC) 优化了干旱土地的智能灌安排. 这种先进的系统提高了作物产量和用水效率 (WUE),与传统方法相比,大大节省了水.
科学领域:
- 农业工程 农业工程
- 控制系统 控制系统
- 水资源管理 水资源管理
背景情况:
- 智能灌计划对于可持续农业至关重要,特别是在缺水的干旱和半干旱地区.
- 优化农业用水是解决全球水资源短缺问题的关键.
- 现有的灌控制方法可能无法充分利用预测能力以获得最大的效率.
研究的目的:
- 为智能灌计划设计和模拟一个模型预测控制器 (MPC).
- 评估MPC对作物产量,用水效率 (WUE) 和番茄生产中的节水效率的影响.
- 将MPC的性能与手动和开环控制策略进行比较.
主要方法:
- 为灌系统开发数学模型,以预测未来的状态.
- 三种控制策略的模拟:手动控制,开环控制和模型预测控制 (MPC).
- 使用完全随机设计 (CRD) 方法对番茄生产的策略进行比较.
主要成果:
- 模型预测控制 (MPC) 实现了最高的平均作物产量 (20 t/ha) 和优越的用水效率 (WUE) (10.4 kg/m3).
- 与手动控制相比,MPC显著节省了水,与手动控制相比,消耗量减少了29%,与开放循环控制相比,减少了8%.
- 在优化灌计划以提高农业成果方面,MPC的表现优于手动和开放循环控制.
结论:
- 模型预测控制 (MPC) 是非常有效的智能灌安排,优化作物产量和节水.
- 拟议的MPC框架为干旱和半干旱地区的农业提供了可持续的解决方案,解决了水资源短缺问题.
- MPC技术有可能对全球粮食安全和可持续水资源管理做出重大贡献.
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