An Improved Model−Free Current Predictive Control of Permanent Magnet Synchronous Motor Based on High−Gain Disturbance Observer

Abstract

Predictive current control (PCC) is an advanced control strategy for permanent magnet synchronous motors (PMSM). When the motor drive system is undisturbed, predictive current control exhibits a good dynamic response speed and steady−state performance, but the conventional PCC control performance of PMSM that depends on the motor body model is vulnerable to parameter perturbation. Aiming at this problem, an improved model−free predictive current control (IMFPCC) strategy based on a high−gain disturbance observer (HGDO) is proposed in this paper. The proposed strategy is introduced with the idea of model−free control, relying only on the system input and output to build an ultra−local current prediction model, which gets rid of the constraints of the motor body parameters. In the paper, the ultra−local structure is optimized by comparing and analyzing the equation of the state of the classical ultra−local structure and PMSM system. The system’s current state variables are incorporated into the ultra−local system modeling, as a result, the current estimation errors existing in the classical ultra−local structure are eliminated. For the unmodeled and parametric perturbation part of the ultra−local system, a high−gain disturbance observer is designed to estimate it in real time. Finally, the proposed IMFPCC strategy is compared with the conventional model−based predictive current control (MPCC) and the conventional model−free predictive current control (CMFPCC) in simulation and experiment. The results show that the current steady−state error of the IMFPCC strategy in the case of parameter variation is only 50% of the MPCC method, which proves the effectiveness and correctness of the proposed strategy.

Model-free three-vector predictive current control of permanent magnet synchronous motor based on improved sliding mode observer

“…Considering the various influencing factors in practice, the PMSM with perturbation mathematical model can be obtained [4]:…”

Effects of Electromagnet Interference on Speed and Position Estimations of Sensorless SPMSM

“…Moreover, its application to nonsalient sensorless surface-mounted PMSM (SPMSM) is difficult. On the contrary, back-EMFs based on machine model for medium and high speed range is usually calculated by observers, such as Luenberger observer [2], [3], [18]- [20], Kalman observer [21]- [23], disturbance observer [24]- [28], sliding mode observer [1], [4]- [8], [11], [29]- [35] and so on [10].…”

Model-Free Predictive Current Control of Five-Phase PMSM Drives

“…The first method is carried out by using the input and output information of systems without any model for prediction [15,16]. The second method uses a model with one or more uncertain terms that should be estimated continually via the input and output data of systems [17][18][19][20][21][22][23]. The last type is devoted to the methods with an ideal model of the plant.…”

“…The ultra-local model is usually studied in conjunction with model-free predictive current control (MFPCC). A nonlinear disturbance observer [17], a linear extended state observer [18], a sliding mode observer [19], and a high-gain disturbance observer [20] have been successively developed to estimate the known and unknown parts of the ultra-local model. Apart from the parameter-free predictive control, the steady-state performance enhancement is considered in [21]; a discrete-space vector modulation is developed for induction motor drives.…”