Research On The Control Of VAV Air Conditioning System Based On Particle Swarm Optimization

With the continuous improvement of people's living standards,air conditioning has become an indispensable part of people's life and work.The subject of variable air volume air conditioning system as the object of study,because of its energy-saving and relatively simple operation of the advantages,more and more popular.At present,the air conditioning system is generally used in the conventional control mode.Under certain working conditions,the traditional conventional control method can still obtain better control performance requirements.However,for VAV air conditioning system,the control performance is limited because of some factors,especially when the air conditioning is started and the working condition is switched.The air conditioning control system is prone to lag.Therefore,this paper proposes the use of swarm intelligence algorithm for tuning.The main research work accomplished in this paper can be divided into the following points:(1)The application of VAV air conditioning system in China and its future development are analyzed,and the information about the application of intelligent algorithm in industry is collected.The fan control mode and terminal device control mode of VAV air conditioning system are analyzed.It is determined that the premise of simulation in this paper is to use variable static pressure fan control mode and terminal pressure-independent control mode.(2)The optimization method based on PSO.The principle of each regulator of PID controller and the method of adjusting PID parameters applied in industry are analyzed.Because the VAV system has the characteristics of time-delay,nonlinearity,nonstationarity and uncertainty,the particle swarm optimization(PSO)algorithm of intelligent algorithm is used to optimize the PID controller(PSO-PID).So that it can get a set to make the air conditioning system operation performance is optimal.(3)The improvement of the elementary particle swarm optimization algorithm.The basic particle swarm optimization algorithm has some disadvantages,such as slow convergence,low precision and easy to fall into the local optimum,and so on.In this paper,the basic particle swarm optimization(PSO)algorithm is weighted and improved,and its effectiveness is verified by simulation and comparative analysis.(4)The research of air supply and room model at the end of air conditioning system.By changing the load of air conditioning room to change the state of air supply and air supply volume,the factors affecting air supply volume are described in detail and the determining point of air supply volume is expressed by curve.The factors affecting room temperature are also analyzed when analyzing the size of air supply.The accuracy of room model determines the performance of the system.(5)Analysis of simulation results.According to the room model,the transfer function of the controlled object is obtained,and the weighted particle swarm optimization algorithm is used to optimize the parameters of the controller.At the same time,the basic particle swarm optimization and the traditional empirical method are used to adjust the parameters of the controller.Compare the results.It is concluded that the particle swarm optimization algorithm with inertia weight proposed in this paper is very suitable for the variable air volume air conditioning system with a variety of characteristics of the application of controller control of this system.Moreover,this method can be applied to other similar industrial control systems by using intelligent algorithm to optimize the controller.