Research And Application Of The Prediction And Decoupling Optimized Algorithm Based On Neural Network

There are lots of complex industrial processes in all walks of life, and all of which are very strong time-varying, nonlinear and uncertainty. In general, precise mathematical model can not be established in such systems. The traditional methods of analysis and control strategies are not able to control the type of object effectively, it is difficult to obtain good control effect and system robustness. On the basis of combining with the traditional analysis method many scholars innovated continuously and combined control and intelligent, began to enter to the advanced stage of intelligent development.Currently, the intelligent control system is to make the transition to comprehensive control, that is to say, the fusion of all kinds of intelligent methods will be a new and efficient development direction in the future development of intelligent control. It can approximate nonlinear system, so which can solve nonlinear systems, and modeling and parameter identification problem of complex systems in the actual production. Combined grey system theory and neural network method to establish grey neural network is presented. This fusion method can make up for the lack of a single model, the small sample data can achieve good prediction effect. On this basis, this article designs a method of the model parameters of grey neural network optimized by genetic algorithm. By utilizing the property of gray model that the randomness of data can be reduced and the strong nonlinearity of neural network, the method establishes a non-linear prediction model for air conditioning demand, and the genetic algorithm is used to optimize it so as to improve the accuracy of forecasting and speed up the degree of convergence. Simulation results indicate that the algorithm can better solve the problem of air conditioner order forecasting and can be widely apply to similar prediction.Regard variable air volume air conditioning system as the research object at the end of the paper, aiming at open question of the end device of the variable air volume air conditioning control process, using the feed-forward compensator method to design the three input-three output decoupling compensator of the VAV air conditioning system and genetic algorithm to optimize PID controller is designed. Results show that the decoupling controller has good control performance and system robustness, provides an effective feasible control method for further research on VAV air conditioning system.