Design Of Magnetic Levitation Fuzzy Control System Based On Particle Swarm Optimizatio

Because there is no direct mechanical contact,the magnetic levitation technology has the advantages of no friction,no lubrication,low power consumption,no pollution and so on.As a kind of high and new technology,the magnetic levitation is mature for development of decades years,and has a wide range of applications in the field of transportation,industry and aviation.As the research object of the magnetic levitation technology,the nonlinear and unstable magnetic levitation ball system is difficult to achieve a good control effect.On the basis of domestic and foreign research,there is good research value to find a better method to control the magnetic levitation ball system.Firstly,the background and significance and control status of the magnetic system is introduced.The linear mathematical model of magnetic levitation system is established based on its structure and working principle.And the conventional fuzzy controller of magnetic levitation system is designed and simulated.Then,the fuzzy control method based on MATLAB/Signal Constraint toolbox is proposed,aiming at the steady state error of the conventional fuzzy control.The fuzzy membership function is optimized to reduce the steady-state error by the Signal Constraint toolbox.The simulation results show that the algorithm is effective and advantageous.What's more,a new method based on particle swarm optimization algorithm is proposed to eliminate the chattering phenomenon in optimization process.The particle swarm optimization algorithm is used to optimize quantization factor and scaling factor of self-tuning fuzzy controller.The simulation results show that the fuzzy control system based on particle swarm optimization has better dynamic performance and stable performance.Finally,by using hardware in the loop simulation device of QuaRC magnetic levitation ball system,Real time control experiment based on the designed fuzzy controller is carried out in the device and the effectiveness and scientificity of the controller is verified.