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Linear Quadratic Optimal Control Applied to the Greenhouse Temperature Hierarchal System

机译:线性二次最优控制在温室温度分级系统中的应用

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Optimal greenhouse temperature management systems as hierarchical systems have been employed to achieve suitable conditions for crop growth. The system is generally decomposed into upper and lower layers. The lower layer usually includes online controllers that try to cancel tracking errors of temperature set points obtained from the upper layer. However, as the greenhouse temperature is highly non-linear, the problem of lower layer controller design becomes very complex and the online computational demands are great, which limit the practical applications of hierarchical systems. This paper presents the design of a practical greenhouse temperature hierarchical control approach. In lower layer, a linear quadratic optimal controller with heater inputs is used. The strategy is based on a linearised model achieved by using an accurate linearisation method for an inside temperature non-linear physical model which can be described as an affine non-linear one. The controller is designed by means of finding a tradeoff between set point tracking and cost requirements reduction. The upper layer calculates optimal temperature trajectories by minimising net costs. Performance of the hierarchical control system is studied in simulation. The results show that the upper layer controller can effectively achieve the set point and that the lower layer controller can contribute to a good control performance with a minor cost increment.
机译:已采用最佳温室温度管理系统作为分层系统来实现作物生长的合适条件。该系统通常分解为上层和下层。下层通常包括在线控制器,这些控制器试图消除从上层获得的温度设定点的跟踪误差。然而,由于温室温度是高度非线性的,下层控制器设计的问题变得非常复杂,在线计算需求很大,这限制了分层系统的实际应用。本文提出了一种实用的温室温度分级控制方法的设计。在下层,使用带有加热器输入的线性二次最优控制器。该策略基于通过对内部温度非线性物理模型使用精确的线性化方法实现的线性化模型,该线性化模型可以描述为仿射非线性模型。通过在设定点跟踪和降低成本需求之间找到折衷的方式来设计控制器。上层通过最小化净成本来计算最佳温度轨迹。在仿真中研究了分级控制系统的性能。结果表明,上层控制器可以有效地达到设定点,而下层控制器可以以较小的成本增加来实​​现良好的控制性能。

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