Sensorless current model control for permanent magnet synchronous motor based on IPID with two‐dimensional cloud model online optimisation

2019 ◽  
Vol 12 (5) ◽  
pp. 983-993
Author(s):  
Haifeng Wei ◽  
Heng Tao ◽  
Fuqiao Duan ◽  
Yi Zhang ◽  
Yuanjiang Li ◽  
...  
Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 65 ◽  
Author(s):  
Meiling Tang ◽  
Shengxian Zhuang

In this study, a current model predictive controller (MPC) is designed for a permanent magnet synchronous motor (PMSM) where the speed of the motor can be regulated precisely. First, the mathematical model, the specifications, and the drive topology of the PMSM are introduced, followed by an elaboration of the design of the MPC. The MPC is then used to predict the current in a discrete-time calculation. The phase current at the next sampling step can be estimated to compensate the current errors, thereby modifying the three-phase currents of the motor. Next, Simulink modeling of the MPC algorithm is given, with three-phase current waveforms compared when the motor is operated under the designed MPC and a traditional vector control for PMSM. Finally, the speed responses are measured when the motor is controlled by traditional control methods and the MPC approach under varied speed references and loads. In comparison with traditional controllers, both the simulation and the experimental results suggest that the MPC for the PMSM can improve the speed-tracking performance of the motor and that this motor has a fast speed response and small steady-state errors under the rated load.


Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 172 ◽  
Author(s):  
Zhihong Wu ◽  
Weisong Gu ◽  
Yuan Zhu ◽  
Ke Lu

Via the vector space decomposition (VSD) transformation, the currents in an asymmetric six-phase permanent magnet synchronous motor (ASP_PMSM) can be decoupled into three orthogonal subspaces. Control of α–β currents in α–β subspace is important for torque regulation, while control of x-y currents in x-y subspace can suppress the harmonics due to the dead time of converters and other nonlinear factors. The zero-sequence components in O1-O2 subspace are 0 due to isolated neutral points. In α–β subspace, a state observer is constructed by introducing the error variable between the real current and the internal model current based on the internal model control method, which can improve the current control performance compared to the traditional internal model control method. In x–y subspace, in order to suppress the current harmonics, an adaptive-linear-neuron (ADALINE)-based control algorithm is employed to generate the compensation voltage, which is self-tuned by minimizing the estimated current distortion through the least mean square (LMS) algorithm. The modulation technique to implement the four-dimensional current control based on the three-phase SVPWM is given. The experimental results validate the robustness and effectiveness of the proposed control method.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 48913-48920 ◽  
Author(s):  
Bo Xu ◽  
Xiaokang Shen ◽  
Wei Ji ◽  
Guoding Shi ◽  
Jian Xu ◽  
...  

2021 ◽  
Vol 11 (22) ◽  
pp. 10840
Author(s):  
Chenhui Zhou ◽  
Feng Yu ◽  
Chenguang Zhu ◽  
Jingfeng Mao

Permanent magnet synchronous motors and their relevant control techniques have become more and more prevalent in electric vehicle driving applications because of their outstanding performance. This paper studies a simple and effective sensorless scheme based on a current observer for a permanent magnet synchronous motor powered by a three-level inverter, which avoids the injection of a high-frequency signal and the observation of back-electromotive force. In this way, a current observer is constructed to observe d–q-axes currents by relying on an extended-current model. Thereafter, the position and speed of the machine can be extracted from two PI controllers associated with the d–q-axes current-tracking errors. Meanwhile, it takes into account the model predictive current control with neutral-point voltage balance to maintain the stability of the three-level inverter system. In general, this scheme realizes sensorless operation in a full-speed domain and is no longer limited by the types of inverter and method used.


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