Combining extended kalman filtering and MPC for advanced induction machine drive systems

This paper presents a high-performance control method for induction machine drives that integrates an Extended Kalman Filter (EKF) and Model Predictive Control (MPC) for fast and accurate speed control. The EKF is utilized to estimate the stator flux and load torque and filter noisy measurements of stator currents and rotor speed, thereby enhancing the system's internal state information reliability and accuracy. These enhanced estimates are utilized in the MPC algorithm to predict system dynamics and compute optimal control inputs. The combined EKF-MPC approach provides improved speed tracking, enhanced disturbance rejection, and robust dynamic performance. Simulation results demonstrate the performance and engineering application potential of the proposed method to advanced induction motor drive applications.

Publication Details

Journal
ARPN Journal of Engineering and Applied Sciences
Published
2025-10-31
DOI
https://doi.org/10.59018/0725131
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
0.00
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article

Combining extended kalman filtering and MPC for advanced induction machine drive systems

ARPN Journal of Engineering and Applied Sciences
Sensorless Control of Electric Motors
article

Combining extended kalman filtering and MPC for advanced induction machine drive systems

article en

Abstract

This paper presents a high-performance control method for induction machine drives that integrates an Extended Kalman Filter (EKF) and Model Predictive Control (MPC) for fast and accurate speed control. The EKF is utilized to estimate the stator flux and load torque and filter noisy measurements of stator currents and rotor speed, thereby enhancing the system's internal state information reliability and accuracy. These enhanced estimates are utilized in the MPC algorithm to predict system dynamics and compute optimal control inputs. The combined EKF-MPC approach provides improved speed tracking, enhanced disturbance rejection, and robust dynamic performance. Simulation results demonstrate the performance and engineering application potential of the proposed method to advanced induction motor drive applications.

ARPN Journal of Engineering and Applied Sciences
Openalex Percentile: Top 68%
Sensorless Control of Electric Motors
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