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    • 9. 发明公开
    • Apparatus for controlling a component implemented in a HVAC distribution system
    • 识别系统
    • EP0721087A1
    • 1996-07-10
    • EP95120057.5
    • 1995-12-19
    • LANDIS & GYR POWERS, INC.
    • Ahmed, OsmanMitchell, John W.Klein, Sanford A.
    • F24F11/00G05B13/02
    • G05B13/027F24F11/30F24F11/54F24F11/63Y10S706/914
    • A controller implemented in a heating, ventilation and air-conditioning (HVAC) distribution system provides improved control by implementing a general regression neural network to generate a control signal based on identified characteristics of components utilized within the HVAC system. The general regression neural network utilizes past characteristics and desired (calculated) characteristics to generate an output control signal. The general regression neural network is implemented in a feedforward process, which is combined with a feedback process to generate an improved control signal to control components within the HVAC distribution system. Implementation of the general regression neural network is simple and accurate, requires no input from an operator supervising the controller, and provides adaptive, real-time control of components within the HVAC distribution system.
    • 在加热,通风和空调(HVAC)分配系统中实施的控制器通过实施一般回归神经网络来提供改进的控制,以基于在HVAC系统内使用的组件的识别特征来生成控制信号。 一般回归神经网络利用过去特征和期望(计算)特征来产生输出控制信号。 一般回归神经网络在前馈过程中实现,其与反馈过程结合以产生改进的控制信号以控制HVAC分配系统内的组件。 一般回归神经网络的实现是简单准确的,不需要监控控制器的操作员的输入,并且可以对HVAC分配系统内的组件进行自适应的实时控制。