Abstract
The performance of conventional direct torque control strategy from the viewpoint of flux and torque ripples has been unsatisfactory. Therefore, this study aims to propose a novel finite-control-set model predictive direct torque control strategy with extended output based on two-step prediction. An appropriate pre-selected vector, which is modulated in a specific manner, is selected through a look-up table and then used to optimise the pre-selected voltage vector based on the computing result from the model prediction and output it. The proposed strategy extends the range of the vectors that can be used to enhance the flux and torque control performance and reduce ripples and computational complexity in comparison with the conventional finite-control-set model predictive direct torque control. The feasibility of the proposed method is verified by conducting a verification test using dSPACE and Tyhpoon HIL 402 experimental platform.
Highlights
Some nonlinear and linear controllers of the complex control systems are proved to be successful in various areas [1,2,3]
With the development of microprocessors, model predictive control has gradually been introduced into the permanent magnet synchronous motor torque control and is being developed into the model predictive direct torque control (DTC) (MPDTC) method
This study proposes a control strategy based on FCS-MPDTC
Summary
Some nonlinear and linear controllers of the complex control systems are proved to be successful in various areas [1,2,3]. With the development of microprocessors, model predictive control has gradually been introduced into the permanent magnet synchronous motor torque control and is being developed into the model predictive DTC (MPDTC) method This method has attracted considerable attention because it can be used to intuitively express the state of important variables and to optimise output; helping to effectively reduce ripples in the output torque [15,16,17,18,19,20,21,22]. Predictive calculations are performed on the pre-selected VSVs and the optimal VSV is selected based on the results obtained to improve flux and torque control performance In this method, the finite set contains 20 different VSVs, and six VSVs are used in performing evaluations in each cycle. After ignoring the stator resistance voltage drop, the optimal VSV is determined using a cost function with the smallest number of control targets This method simplifies the algorithm while optimising flux and torque performance. A comprehensive experimental platform based on dSPACE and Typhoon HIL 402 is established in Section 5 to verify the feasibility of the proposed control method
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