基于模型的预测温室气体参数控制水族系统的aquaponic系统.
Pragnaleena Debroy1, Priyanka Majumder2, Amrit Das3
1Department of Electronics and Instrumentation Engineering, National Institute of Technology Silchar, Silchar, Assam, India.
概括
这项研究引入了一种新的双层控制战略,用于水生温室,优化气候参数,以增强植物生长和系统可持续性. 该系统使用粒子群优化和受约束的离散模型预测控制来实现卓越的性能.
科学领域:
- 农业工程 农业工程
- 环境控制系统环境控制系统
- 水上培养和水上培养学
背景情况:
- 水系统需要精确的环境控制,以实现最佳的鱼类和植物健康.
- 温室环境允许调节温度,二氧化碳,湿度和光线.
- 有效的控制策略对于最大限度地提高水产养殖系统的生产力和可持续性至关重要.
研究的目的:
- 开发和验证水产温室系统的新型控制方法.
- 保持最佳的温室气候参数 (温度,二氧化碳度,湿度).
- 为了提高水产养殖系统的性能,利能力和可持续性.
主要方法:
- 一个双层控制策略,将粒子集群优化 (PSO) 结合为设定点优化和受约束的离散模型预测控制 (CDMPC) 用于轨迹跟踪.
- 将PSO与基因算法 (GA) 进行设定点优化的比较.
- 使用相对平均偏差 (RAD) 和平均相对偏差 (MRD) 的比例整合 (PI) 控制器对CDMPC性能的评估.
主要成果:
- 拟议的CDMPC控制器与PI控制器相比表现出更高的性能,温度,CO2和湿度的RAD和MRD值明显较低.
- PSO和GA表现出类似的计算效率,采用了PSO的最佳值.
- CDMPC控制器表现出强度,高效的设定点跟踪和有效的干扰排斥.
结论:
- 开发的双层控制策略有效地维持了水产养殖学最佳温室气候参数.
- 这种方法提供了一种有前途的技术,可以促进水产养殖生产,利能力和可持续性.
- 控制器在环境监管中的效率可以导致提高产量和减少劳动力需求.
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