Based On Adaptive Pid Neural Network And The Application Of Intelligent Control In The Fresh Air System

In recent years solar wind system appeared, it uses clean solar energy, has for the interior ventilation, as well as heating indoor air conditioning system function model, is clean and no pollution, energy saving, and has broad application prospect.The system is a complex nonlinear, time-varying system, it is difficult to establish the precise mathematical model, so the traditional classical control algorithm is difficult to achieve good control effect, in order to obtain better effect in this paper, a variety of intelligent control strategy is used. Fresh air system can be affected by environmental factors such as air temperature, external environment factors such as solar radiation intensity, which will bring a lot of influence to the control parameters. While most of the control theory for nonlinear systems, such as fuzzy control algorithm has more experience requirements, in order to improve universality and applicability of the intelligent control algorithm, this paper studies applicability of the fresh air control system in more detail, to reduce relying on human and improve the system adaptability.The main contents are as follows:1. After having a preliminary understanding of the experimental platform, fresh air system experimental platform is used for control experiment of different operation modes in different operation stages to obtain a more comprehensive air system operating characteristics and control rules. It includes:the relationship between air temperature and control voltage, inverter control voltage’s range, air temperature’s range, relationship between hot water temperature and air temperature, characteristics of system switching mode, providing adequate experimental data and control experience;2. Secondly, after analyzing the characteristics of fresh air system, fuzzy control is used to control the system, to show that the system is nonlinear and the general intelligent control algorithm relies on a large number of people experience etc;3. The adaptive PID control algorithm is used on fresh air system to reduce human intervention with self learning control;4. According to the different characteristics of fuzzy control and neural network control algorithm, two intelligent control strategies are combined to give full play to their advantages. A fuzzy neural network is built through the test of the training sample. Trying the fuzzy rule self establishment and correction, a control system is proposed based on neural network self learning fuzzy rules; 5. A BP neural network is established to use its characteristics of nonlinear mapping and self-learning, and an adaptive neural network control strategy of solar fresh air system is proposed, with analysis of the system model and designing of adaptive neural network controller.