A Deadbeat Predictive Current Vector Control Algorithm for Improving Current Control Performance of Stepper Motors.

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Bibliographic Details
Title:	A Deadbeat Predictive Current Vector Control Algorithm for Improving Current Control Performance of Stepper Motors.
Authors:	Ma, Jianmin¹ mw696@163.com, Ma, Kexin²
Source:	Progress in Electromagnetics Research C. 2026, Vol. 163, p277-284. 8p.
Subjects:	Stepping motors, Numerical control of machine tools, Real-time computing, Stability theory, Electric motors, Predictive control systems, Pulse width modulation
Abstract:	To address the issues of step loss, control lag, and low precision in open-loop hybrid stepper motors applied in economical CNC machine tools, a deadbeat predictive current field oriented control method (DPCFOC) is proposed. First, the research progress of hybrid stepper motor vector control is systematically reviewed, analyzing the advantages and limitations of existing schemes in error compensation, model construction, and algorithm implementation. Subsequently, the continuous mathematical model of the hybrid stepper motor in the rotating coordinate system is established, and the discrete deadbeat predictive model and current prediction equation are derived using the first-order forward Euler method. On this basis, a deadbeat vector control algorithm is proposed. Compared with the traditional dual-closed-loop vector control with PI regulators, the algorithm predicts the next-step current through the motor model and calculates the optimal reference voltage vector in advance to eliminate current error, thereby improving dynamic response speed. Stability analysis via Z-transformation reveals that the system remains stable when the model inductance parameter is within 0-2 times the actual inductance. For the two-phase hybrid stepper motor, a space vector pulse width modulation (SVPWM) strategy based on a dual H-bridge inverter is designed, using 4 non-zero vectors and 2 zero vectors to synthesize the desired voltage vector. Finally, an experimental platform is built with a TMS320F28335 controller and a 57CME22A closed-loop stepper motor to verify the algorithm. This study provides a feasible solution for improving the control precision and dynamic performance of hybrid stepper motors in economical CNC machine tools. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	To address the issues of step loss, control lag, and low precision in open-loop hybrid stepper motors applied in economical CNC machine tools, a deadbeat predictive current field oriented control method (DPCFOC) is proposed. First, the research progress of hybrid stepper motor vector control is systematically reviewed, analyzing the advantages and limitations of existing schemes in error compensation, model construction, and algorithm implementation. Subsequently, the continuous mathematical model of the hybrid stepper motor in the rotating coordinate system is established, and the discrete deadbeat predictive model and current prediction equation are derived using the first-order forward Euler method. On this basis, a deadbeat vector control algorithm is proposed. Compared with the traditional dual-closed-loop vector control with PI regulators, the algorithm predicts the next-step current through the motor model and calculates the optimal reference voltage vector in advance to eliminate current error, thereby improving dynamic response speed. Stability analysis via Z-transformation reveals that the system remains stable when the model inductance parameter is within 0-2 times the actual inductance. For the two-phase hybrid stepper motor, a space vector pulse width modulation (SVPWM) strategy based on a dual H-bridge inverter is designed, using 4 non-zero vectors and 2 zero vectors to synthesize the desired voltage vector. Finally, an experimental platform is built with a TMS320F28335 controller and a 57CME22A closed-loop stepper motor to verify the algorithm. This study provides a feasible solution for improving the control precision and dynamic performance of hybrid stepper motors in economical CNC machine tools. [ABSTRACT FROM AUTHOR]
ISSN:	19378718
DOI:	10.2528/PIERC25101602