This paper proposes a scheme of space vector optimization for model predictive control (MPC) of dual three-phase permanent magnet synchronous machine (DTP-PMSM), which aims to restrain the current harmonics under the condition of low inductance. The multiphase electric motor possesses the characteristics of quick current variation rate by means of the low inductance. Especially incorporating with MPC schemes, its advantage of quick response shows promising prospects for various applications such as robotics, aerospace and medical devices. However, such a characteristic of low inductance requires shorter control period, which means that the traditional MPC cannot be implemented to suppress the current harmonics since the performance of the power switching devices and the digital controller limits the arbitrary increasing of the control frequency. This paper presents the space-vector-optimized model predictive control (SVO-MPC) for DTP-PMSMs with low inductance by pre-synthesizing space vectors to eliminate harmonics and optimizing the zero vector to deal with quick current response. As a result, the proposed SVO-MPC can remarkably improve the steady and dynamic control performance, while the traditional MPC almost fails at commonly-adopted control frequency. Lastly, simulated and experimental results are both given to verify the feasibility of the proposed SVO-MPC for DTP-PMSMs with quick current response.
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This paper proposes a scheme of space vector optimization for model predictive control (MPC) of dual three-phase permanent magnet synchronous machine (DTP-PMSM), which aims to restrain the current harmonics under the condition of low inductance. The multiphase electric motor possesses the characteristics of quick current variation rate by means of the low inductance. Especially incorporating with MPC schemes, its advantage of quick response shows promising prospects for various applications such...
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