Modified model predictive torque control for a PMSM‐drive with torque ripple minimisation

Abstract

This paper presents an improved model predictive torque control (MPTC) scheme for a permanent magnet synchronous machine (PMSM). In conventional finite set model predictive control (FS-MPC), the optimal voltage space vector (VSV) is selected for application in the voltage source inverter (VSI) by the evaluation and minimisation of a cost function; however, the application of a single VSV in the whole control cycle leads to a relatively high torque ripple and a high sampling time is necessary to overcome this issue. In order to reduce these shortcomings without sacrificing torque reaction performance, a modified MPTC is proposed. First, in order to reduce the computational burden, a switching table is introduced for a reduction in the selection of the possible VSVs; further, to reduce the torque ripple, the duty cycle optimisation of a subset of VSVs available from the VSI is performed. The conventional FS-MPC and the proposed control scheme are implemented using a field programmable gate array, and are experimentally compared in terms of torque and flux ripple, current harmonics, and computational effort.

Applying a modified model predictive current control method to improve surface‐mounted permanent magnet synchronous motor drives performance in transient and steady‐state operations

“…The d and q axes current values at the end of the control cycle are calculated through (13) and (14)…”

“…In this method, the proper voltage vector (VV) is selected through the cost function (CF), which leads to the best response among those available. Both the flux and torque, as control variables in PMSM drives are the most well-known features of the FCS-MPC method [6][7][8][9][10][11][12][13], which is briefed here as model predictive torque control (MPTC). In the MPTC method, the proper VV that leads to the best torque and flux response is selected among the feasible ones through the CF.…”

“…One of the other major defects in MPTC is the fact that adjusting the weighting factor is difficult because flux and torque errors in the CF differ in both the unit and magnitude, consequently, an appropriate weighting factor is required to assure proper performance. Although there exists some methods based on fuzzy strategy, multi-objective optimisation, and other solutions for adjusting or eliminating the weighting factor, this issue is an open problem [11][12][13].…”

Robust cascade‐free predictive speed control for PMSM drives based on Extended State Observer

“…During recent years, the finite control set model predictive control (FCS‐MPC) strategy has emerged as an attractive solution for permanent magnet synchronous motor (PMSM) and power converters due to its intuitive concept, great flexibility and fast dynamic response [1–3]. The FCS‐MPC predicts the future behaviour of the system states in each sampling instant based on the system model and selects the optimal actuation according to predefined optimization criteria (cost function) [4–6].…”

Optimal torque control of permanent magnet synchronous motors using adaptive dynamic programming

“…Recently, there has been research on more advanced control approaches for PMSMs, such as sliding mode control [12–14], model predictive control (MPC) [3, 15–18], adaptive control [19, 20], fuzzy control [21, 22] and neural network control [23, 24]. Each of these controllers offers some improvement in the performance of PMSMs.…”