Fuzzy Neural Network Control Of VAV And EMS-500 Building Integrated Control System Is Studies

Air conditioning system is an important part of modern architecture, VAV because of its energy saving effect is good, control, flexible, and other advantages more and more attention. Only reasonable and effective control system design, can reflect the greatest degree of VAV systems, namely the advantage of comfort and energy-saving characteristics. Because of the variable air volume (VAV air conditioning system of nonlinear and person lag, the precise model harder-to-get or can't get, so in VAV control, classical control method can realize effective control, using intelligent control can overcome shortcomings of classical control, can probes VAV air conditioning realize effective control. In intelligent control method, fuzzy control system has being easy to understand the expression way, but difficult to automatically generate and adjust membership functions and fuzzy control rules, The neural network has stronger adaptive learning ability, but the income of input and output relationship cannot easily acceptable manner. Fuzzy logic and neural network combined with neural network, the absorption fuzzy logic and the advantages of both, and overcome the short coming, each has a good VAV system of intelligent control method. Meanwhile, in order to explore the specific process realized intelligent method, it is necessary to engineering application of VAV controlling the Lou Ning control system were studied.In this paper, a large number of documents reviewed based on the air conditioning control system, and aiming at the existing problem of a series of research. Firstly introduces VAV system of basic content and existing problems, Secondly, in the control method of design, consider to air conditioning system is a large inertia, time delay, and makes it hard to establish a system of mathematical model, therefore, adopts the advanced intelligent control method, the fuzzy neural network control of the air conditioning system is controlled. Based on fuzzy control and neural network control the advantages and disadvantages of both the combination of VAV systems, the application of the fuzzy neural network control method. That is, based on the fuzzy system structure, neural network learning algorithm introduces fuzzy control system, the decision equivalent structure neural network, neural network of each layer and each node is corresponding fuzzy part of the system. By using the neural network learning, adjust the fuzzy set membership functions of central values and width values, adjusting the on-line subordinate function shape, realized the VAV system of room-temperature fuzzy adaptive control. The simulation results show that the controller parameters optimization of evolution, a fuzzy neural network has better dynamic characteristic and robustness, is applied to VAV control system of the new method, air conditioning system with the change of environment, always maintain optimal parameters operation. Through the introduction of the variable air volume air conditioning control system hardware and software implementation method and in the new project of installations, realize integrating comfortable, high efficiency, energy saving effects at a suit air conditioning system control scheme. In order to fully consider the administration of energy conservation effect, this paper studies will air conditioning system with BMS system to control the information integration, excellent performance and has good energy-saving.