A robust permanent-magnet synchronous motor drive for aerospace applications
Permanent Magnet Synchronous Motors (PMSM) are problematic to control due to their lack of effectiveness in high-performance control methods with its problems involving Inertia, Torque Ripple and Current controls. The goal of this study is to reduce the torque ripple observed in the PMSM's low-...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/167071 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Permanent Magnet Synchronous Motors (PMSM) are problematic to control due to their lack of effectiveness in high-performance control methods with its problems involving Inertia, Torque Ripple and Current controls. The goal of this study is to reduce the torque ripple observed in the PMSM's low-speed parameters because it is one of the major issues that arises in PMSM. In an active disturbance rejection control (ADRC) speed control system, a Radial Basis Function Neural Network (RBFNN) is employed as a torque compensator in conjunction with a second order extended state observer (ESO) to reduce torque ripple on the control system in PMSM. The neural network parameters are updated in accordance with the adaptive law found using the Lyapunov function to ensure the stability of the closed-loop system. The PMSM drive was simulated in the program MATLAB Simulink. The simulated results show that the proposed method is able to suppress torque ripples and improve the robustness and dynamic response of the system. |
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