A sampling time study for model predictive control in induction motor using processor-in-loop verification
This paper examines the impact of sampling time variation on Model Predictive Control (MPC) when it is applied to Induction motors (IM). Sampling time is a vital element in digital controllers, and selecting the appropriate value can be challenging. MPC is a model-dependent digital controller, which...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
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2022
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| Summary: | This paper examines the impact of sampling time variation on Model Predictive Control (MPC) when it is applied to Induction motors (IM). Sampling time is a vital element in digital controllers, and selecting the appropriate value can be challenging. MPC is a model-dependent digital controller, which is highly affected by sampling time as well as the discretization technique employed by the hardware implementation. Hardware typically uses a discrete controller, and the sampling time and the discretisation method are important factors in the performance. The study proposes utilizing PIL verification with a variety of discretisation methods and sampling times with MPFOC to monitor the performance of the microcontroller. The optimal sampling time is selected by using a numerical optimization method within several test results. The optimisation results found that using a 25 μ s sampling time with the proposed discretisation method will achieve an enhancement of 16% in total in terms of calculation time and accuracy as compared with conventional Euler’s method. |
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