Research On High Accuracy Closed-loop Drive Control System And Experiment Of Two-phase Hybrid Stepping Motor

Stepping motor is a driving device that converts the input electric pulse signal into angular displacement or linear displacement.Because the input pulse is proportional to the rotation angle,stepping motor is widely used in digitally controlled open-loop control systems.However,problems such as low-frequency oscillation,out-of-step locked-rotor,and low efficiency may occur,stepping motor cannot meet higher accuracy control requirements.In this respect,this thesis aims at the existing problems in the control of stepping motors,with the goal of pursuing higher accuracy,high dynamic response,high load capacity,and the closed-loop servo control system of the two-phase hybrid stepping motor is deeply studied.The research object of this thesis is a two-phase hybrid stepping motor.The subdivision control technology is adopted for the phase current,the intelligent control algorithm is applied to the position and speed loop controller of the stepping motor,PID parameters are adjusted online by using an adaptive neuro-fuzzy inference system to achieve high-performance closed-loop servo control of the stepping motor.Adaptive network-based fuzzy inference system uses a hybrid learning algorithm combining BP back propagation algorithm and least square method to automatically train the fuzzy membership function and fuzzy control rules,thereby adjusting PID parameters adaptively.The system model is built using the Simulink platform in MATLAB,and the position and speed closed-loop control scheme of the two-phase hybrid stepping motor is simulated.According to the simulation results,the dynamic and steady-state response characteristics,control accuracy and robustness of the adaptive neuro-fuzzy PID controller are superior to those of the conventional PID controller.In order to verify the feasibility and practicability of this control scheme,the STM32F103ZET6 chip is selected as core control device in this thesis,the TB67S109 A chip is used as drive chip,the 600-line incremental photoelectric encoder and screw drive are installed.The main control module,drive module,serial communication module and other parts of the hardware circuit are designed in this system,the software application layer is configured by using the Keil programming environment.The entire experiment platform is built,and the system function is tested and analyzed.Through the analysis of experimental data,the two-phase hybrid stepping motor speed and position closed-loop control system based on adaptive network-based fuzzy inference system PID control designed in this thesis has dynamic and steady-state performance and anti-load disturbance ability,which can meet some high-performance applications.The experimental results are basically consistent with the theoretical simulation results,which have achieved the expected purpose and have broad application prospects.