Fuzzy Control And Adaptive Fuzzy Neural Network Control In The Solar Air System

The application of solar air system in the modern building heating has become a hot spot. In particular, combination of the phase change material (FCM) and fresh air system is rare in domestic research. In order to save resources, protect environment, and improve the efficiency of energy. In this paper, a fresh air system has been carried out for theoretical analysis and experimental research.This article has set up two solar air systems, which are an experimental platform and a simulating platform. The structure of simulating fresh air system was designed in early stage, and operation modes and fuzzy control method were proposed. For different models, a couple of fuzzy controllers have been designed. Furthermore, the superiority of its control performance was also proved by the experimental data. In the latter part of the work, taking an experimental platform as the object of study, with the help of fuzzy controller design experience and theoretical research on the simulating system in early stage, it is easier to design a more rational structure of the system, operation modes and fuzzy controllers. In order to improve the efficiency of the development of intelligent control systems, and an adaptive fuzzy neural network (AFNN) has been proposed and completed. The main contents are as follows:A fresh air simulating platform has been established firstly. And then the working principle of the system was been introduced. Based on the actual application environment, in this system, four operating modes were planned out, and structure for each model was also described in detail. Meanwhile, the suitable model of a fuzzy controller was selected for this simulating system. According to the control requirements, a couple of fuzzy controllers under different modes were designed. By the treatment of experimental data analysis, the feasibility of the fuzzy control was proved.Scondly, a fresh air Experimental platform has been established. In terms of structure and control, this paper has compared with the simulating system and experiment platform, and also described the system parameters measured and processed. Then, analysis of the needs of the system operating modes, and the design of the structure of each mode were completed. Meanwhile, by processing and analysis of experimental data, the fuzzy controllers'superior control performance was proved.Afterwards, base on the fresh air Experimental platform, using the complementary nature between fuzzy logic and neural network, an adaptive fuzzy neural network was researched, and experimental results showed the rationality of the design.Fourthly, using the LabWindows/CVI development tools, a monitoring interface of solar fresh air system was established, and the function of automatic switching between different modes was achieved. To improve the efficiency of the designs of fuzzy controllers, with the help of ActiveX technology, this paper called fuzzy toolbox.Finally, within both of a simulating platform and experimental platform, a lot of manual operation tests and automatic run experiments were done. Also, by analysis of experimental data, this paper continued to improve the structure and control algorithm of fresh air system.