A Fast Response Robust Deadbeat Predictive Current Control for Permanent Magnet Synchronous Motor

Abstract

Deadbeat predictive current control (DBPCC) has the characteristic of fast current response, but it is sensitive to motor parameters. Observer-based DBPCC can eliminate the steady state current tracking error when parameter mismatch exists. However, the actual current will deviate from the reference current during transient state in the case of inductance mismatch. In this paper, a fast response robust deadbeat predictive current control (FRRDBPCC) method is proposed for surface mounted permanent magnet synchronous motor (SPMSM). Firstly, the current tracking error caused by inductance mismatch during transient state is analyzed in detail. Then, an extended state observer (ESO) is proposed to estimate the lumped disturbance caused by parameter mismatch. Based on discrete time ESO, the predicted currents are used to replace the sampled currents to compensate for one-step delay caused by calculation and sampling. Furthermore, an online inductance identification algorithm and a modified prediction model are proposed. The dq-axis currents can be completely decoupled by updating the inductance in the modified prediction model online, ensuring that the current can track the reference value in two control periods. The proposed method improves robustness against parameter mismatch and guarantees dynamic response performance simultaneously. The experimental results verify the effectiveness of the proposed method.

Enhanced deadbeat predictive current control with novel generalized space vector modulation for five‐level inverter fed permanent magnet synchronous motor drive with reduced torque ripples and less computational burden

“…The dynamic performance of PMSMs, characterized by their rapid response to transient conditions, is particularly critical for applications demanding precise speed and position control, such as robotics, electric vehicles, and high-performance industrial systems. [1][2][3] The stator current directly influences the torque production in PMSM, and their precise control becomes paramount to ensure desired torque performance and fast dynamic response. In order to realize this, many current control techniques have been proposed such as proportional-integral (PI) control, hysteresis current control, sliding mode control (SMC), artificial neural network (ANN)-based control, 4,5 and model predictive control (MPC).…”

“…Permanent magnet synchronous motors (PMSMs) have garnered significant attention in the realm of electric drive systems, owed largely to their salient advantages like high power density, superior efficiency, and a compact footprint. The dynamic performance of PMSMs, characterized by their rapid response to transient conditions, is particularly critical for applications demanding precise speed and position control, such as robotics, electric vehicles, and high‐performance industrial systems 1–3 …”