变风量空调系统协调控制
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摘要
变风量空调系统以其节能性、灵活性而优于其它空调系统,逐渐成为空调系统设计的主流。但是,由于变风量空调系统的控制过程是一个大惯性、纯滞后、非线性、强耦合的复杂系统,应用常规PID控制不能达到理想的控制效果,其在国内的应用还非常有限,为了实现节能的目标,提高国内空调系统的能源有效利用率,所以,研究新型的变风量空调系统控制方法显得尤为重要。
     本文简单地介绍了变风量空调系统的控制原理,根据变风量空调系统主要控制回路的数学模型,从变风量空调系统的控制策略切入,对送风温度控制回路,主要进行了PID控制、模糊自适应PID控制、史密斯预测控制、单神经元自适应PID控制和动态矩阵控制的研究,再针对变风量空调系统送风温度回路、送风管道中的静压点的静压回路、室温回路、空气中二氧化碳浓度回路等四个主要回路之间的耦合,进行了对角矩阵法与神经网络自适应解耦算法进行解耦控制的研究。
     在理论分析的基础上,通过MATLAB仿真,与传统PID控制效果相对比,证明对角矩阵法与神经网络自适应解耦算法都可以有效地消除或减弱系统之间的强耦合,系统响应时间短,并且具有良好的自适应性、鲁棒性。
Variable air volume (VAV) air-conditioning system is superior to the other air-conditioning systems for its economic and flexible performance, which has been the main current of air-conditioning system effectively. However, the VAV air conditioning control system is a great inertia, pure lag, high nonlinear and strong coupling complex system, so the conventional PID control can't obtain a perfect result, and its application in China is still very limited. In order to achieve targets for energy conservation, and improve energy efficiency utilization of domestic air-conditioning system, so, it's particularly important to research the control method of VAV air-conditioning system.
     This paper simply introduced the controlling principle and according to the mathematic model of the main control loop of VAV air-conditioning system, From the control strategy of VAV air-conditioning system, to supply air temperature control loop, mainly adopt PID control、fuzzy adaptive PID control、Smith predictive control、adaline adaptive PID control and dynamic matrix control, and then for the coupling of the main four-loop, the supply air temperature loop、air supply duct static pressure of the static pressure points loop、indoor temperature loop、the air concentration of carbon dioxide, of the VAV air-conditioning system, use the method of the diagonal matrix method and neural network adaptive decoupling algorithm decoupling control to study.
     Basis on the analysis theory, through MATLAB simulation test, compared to the traditional PID control, prove that the diagonal matrix method and neural network adaptive decoupling algorithm decoupling algorithm can effectively eliminate or reduce the strong coupling between the system, the response is very fast, and the system has a good self-adaptability and robustness.
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