The Modeling And Simulation Of Air-Conditioning Control System Based On Neural Network

From the point of view for practical uses, the modeling and simulation of air-conditioning control system based on neural network are researched in this dissertation. Moist air parameter and switching working condition models on neural network are built, the design theory of neural networks and the estimations of linear systems and nonlinear systems with dead time using neual network are discussed, dynamic simulation for aircondition system and predictive control strategies using neural networks are proposed. The simulation experiments are made.The main research work and contributions of this dissertation are as follows: A survey of air-conditioning technique based on artifical neural networks is summarized, and present some points of view about simulation of air-conditioning control system. The paper builds the simulation model based on analyzing the whole year switching working condition, providing the method of the switching working condition realizing, and made it more quickly and effectively. Based on identifying the time-delay system of HVAC, the paper researches the linear and nonlinear systems identification methods with MATLAB system identification toolbox and neural network theory. According to the result of simulation, neural network has obvious advantage for nonlinear systems identification. Because ANN-predictive control can offer good performance, be understanded easily and robustness to the model uncertainly, ANN-predictive control strategies have received much attention and been applied in industries widely. In this dissertation, ANN-predictive control based on time-delay system of air-conditioning is studied and simulated, and good performance is obtained The paper builds the model of the whole year working, the simulation result shows that according to the variety of inside and outside parameter, the model can switch working condition automatically, choose the right working equipment, calculate the equipment capacity, display the cure of temperature variety.