High-Speed Sensorless Control Strategy for Dual Three-Phase Linear Induction Motors Based on Nonlinear Kalman Filter

As the core thrust output component of electromagnetic drive systems, the Dual Three-Phase Linear Induction Motor (DT-LIM) places stringent requirements on the stability and reliability of its control system, and its sensorless control strategy has emerged as a research hotspot. However, as the motor operating frequency increases and the control carrier ratio decreases significantly, conventional algorithms lack sufficient capability to suppress process noise during model discretization, leading to a severe degradation of their observation performance. To address this issue, this paper proposes a Nonlinear Kalman Filter (NLKF) based on the Improved Euler (IE) discretization, which mitigates the model’s process noise at the source of discretization. Through stability and convergence analyses, the feasibility of the proposed algorithm and its advantages in terms of error convergence bounds are verified. The correctness of the theoretical derivations is confirmed through simulations. Furthermore, an experimental platform is established to compare the proposed algorithm with commonly used Kalman filters. A comprehensive analysis is conducted from the perspectives of online observation performance, closed-loop control performance, and computational complexity, thus verifying the proposed algorithm’s performance advantages.