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Global Optimization of VAV Air Conditioning System

机译:变风量空调系统的全局优化

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Energy conversation is a goal of optimal control of Heating, ventilating and air-conditioning (HVAC) system. HVAC is a multi-variable, strongly coupled, nonlinear, time variant large-scale system composed of several subsystems. In this paper, a variable air volume (VAV) air-conditioning system is wholly analyzed with large-scale system theory based on “decomposition and coordination” strategy, and is partially controlled with iterative learning control (ILC) to improve the transient process. The dynamic and steady-state models were built for dynamic characteristic improvement and global optimal control, respectively. For the evaluation of the control policy, the physical tests were implemented on HVAC experimental platform. Results show that all control subsystems work coordinately with “decomposition and coordination” strategy under variable loads. The good performance of subsystems can be maintained under ILC strategy when working points change with the dynamic load.
机译:能量转换是优化控制供暖,通风和空调(HVAC)系统的目标。 HVAC是由多个子系统组成的多变量,强耦合,非线性,时变大型系统。本文基于“分解与协调”策略,利用大规模系统理论对可变风量(VAV)空调系统进行了全面分析,并通过迭代学习控制(ILC)对其进行部分控制以改善过渡过程。建立动态模型和稳态模型分别用于动态特性改进和全局最优控制。为了评估控制策略,在HVAC实验平台上进行了物理测试。结果表明,在可变负载下,所有控制子系统均采用“分解与协调”策略协同工作。当工作点随动态负载变化时,可以在ILC策略下保持子系统的良好性能。

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