RBF (radial basis function) neural network-based indoor visual environment control system and method

Abstract

The invention provides an RBF (radial basis function) neural network-based indoor visual environment control system and method. The system includes a data acquisition module, a data processing and control module and an output driving module; the data acquisition module is used for acquiring indoor and outdoor illuminance values; the data processing and control module is used for obtaining indoor illumination control parameters according to the illuminance values and based on an RBF (radial basis function) neural network algorithm and outputting the indoor illumination control parameters; and the output driving module is used for controlling indoor shutter blinds to rotate and/or an indoor lighting lamp to be turned on according to the indoor visual control parameters so as to realize an indoor visual environment comfortable control effect. According to the RBF (radial basis function) neural network-based indoor visual environment control system and method of the invention, the relatively reasonable indoor visual environment neural network control system is constructed, the control precision and universality of the indoor visual comfortable environment control system can be improved, defects such as instability and limitations of a traditional control system and method can be eliminated; and illumination power resources can be saved to the greatest extent with indoor visual comfort ensured.

Description

technical field [0001] The present invention relates to the field of intelligent control, and more specifically, relates to an indoor visual environment control system and method based on RBF neural network. Background technique [0002] Since the energy crisis in the 1970s, energy and environmental issues have received great attention from all walks of life. The increase in global energy consumption is much higher than economic growth. As the world's largest energy-consuming country, energy consumption is an urgent need for China to pay attention to and solve it. key issues. Building energy consumption accounts for a considerable proportion of the world's total energy consumption. According to the latest survey, in the total energy consumption of the third level, the energy consumption of lighting equipment accounts for 40% to 70%. Therefore, the use of lighting and shading systems to create The indoor visual comfort environment with the least energy consumption is extreme...

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Problems solved by technology

[0005] However, most of the above-mentioned control systems are based on establishing mathematical models and designing theoretical algorithms to achieve control goals. Indoor light environment control requires a control strategy that combines the application of control theory with intelligent control of indoor light environment; Determination requires more experience in environmental control, and fuzzy rules and membership functions are difficult to adjust, and the control system mostly achieves the so-called optimal illuminance value by adjusting the preset illuminance value, which does not take into account the diversity and different visual comfort of users. Uniformity, with limitations

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