Performance Analysis of Current Control Strategies for Hybrid Stepper Motors

Abstract

Hybrid stepper motors are widespread in industrial automation due to their robustness and high torque performance in low speed range, e.g. 3D printers, pick and place, and generally in many low power positioning applications. In order to increase the efficiency and dynamic performance, current/speed/position closed loop controls are implemented for high performance sensored stepper drives. The main challenge comes from the high number of magnetic poles which these motors feature, increasing the ratio between the fundamental and switching frequency. This paper critically evaluates four current control structures based field oriented control: classic PI regulators, sliding mode control, deadbeat predictive current control and model predictive current control. Simulations and experimental results aim to evaluate the dynamic performance, phase current amplitude and distortion in order to support the critical comparison.

Field-Oriented Control of Stepper Motor with Model Predictive Current Control

“…Therefore, the effects of leakage, saturation, hysteresis, and eddy currents are ignored to simplify the model. The model of stepper motor in the d-q coordinate system can be written in the following form: (1) where ud and uq are the voltages of d and q axes; Rs is the winding resistance; id and iq are the currents of d and q axes; Ld and Lq are the inductances of d and q axes; ωe is the rotational speed in its electrical form; ωr is the mechanical rotational speed; Ke is back electromotive force coefficient.…”

“…Hybrid stepper motors (HSMs) are widely used in industrial applications, such as 3D printers and robotic arms, due to their low cost, high reliability, and easy implementation of open-loop control [1,2]. However, although some improved open-loop control methods have improved the smoothness of open-loop operation to some extent [3], openloop control still has some drawbacks and cannot meet the demand for higher accuracy.…”

“…For the FOC algorithm, for improving the control performance to meet different complex occasions, in addition to the conventional proportional-integral (PI) control, various control strategies have been proposed by researchers, such as fuzzy control, sliding mode control (SMC) [1], robust control [6], and model predictive control (MPC) [7]. Deeply rooted in industrial applications, MPC has received significant attention due to its simple implementation [8], effective handling of nonlinearities and constraints, and excellent dynamic performance [9,10].…”