Research On Modeling And Intelligent Control For Boost Convertor Based On FPGA

As the basis of switching power supply research, DC/DC convertor modeling analysis is one of great importances in analysis and design of switching power supply. This paper analyzed the modeling of Boost convertor. The modeling contributes to the improvement for the performance and efficiency of switching power supply.After analysis current of DC/DC modeling, a state-space modeling method based on the Boost convertor is presented. The modeling of the continuous current mode and discontinuous current mode is taking Boost convertor as example. Simulate model is established in Matlab and Vissim in order to meet different requirements. The equivalent circuit modeling and a small-signal modeling are referred based on the state-space model for Boost convertor to meet the requirements of frequency domain and time domain analysis. Moreover, this paper constructs the Takagi-Sugeno fuzzy model of the Boost convertor in CCM (continuous current mode) and DCM (discontinuous current mode) separately. The simulation results have indicated the T-S fuzzy modeling accuracy.In the aspect of controller desighing, this paper refers to the linear control method focusing on the PID control algorithm, and gives a detail expression to the basic principles of commonly used methods of setting the controller parameters. Finally a PI controller based on the method of critical sensitivity approach of tuning is designed and the closed loop simulation is carried out.In-depth study of Takagi-Sugeno fuzzy theory and modeling, the controller for Boost convertor in CCM and DCM are designed. The simulation results indicate the T-S fuzzy controller is better than PI controller.In-depth study of the linear and Takagi-Sugeno fuzzy control methods for Boost convertor, a closed-loop control experiment platform for Boost convertor is designed. According to the FPGA control circuit, the use of VHDL (hardware description language), and SG (System Generator) design processes are introduced respectively. Finally, the linear and T-S fuzzy controllers by combining VHDL and SG are simulated.