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Simultaneous State and Speed Estimation in Linear Induction Motors Using Adaptive High Order Sliding Modes Approaches
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DOI：10.1109/tvt.2026.3666931.png)
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Abstract
En 中文
Linear Induction Motor (LIM) is widely used in rail transit, precision positioning, and industrial automation due to its high efficiency, simple structure, and low maintenance cost. However, the dynamic performance of linear induction motors is affected by nonlinear characteristics and parameter variations, making accurate state and speed estimation crucial for achieving higher performance control. Traditional estimation methods often have limitations and are difficult to meet the increasing demand for control accuracy. In this paper, an adaptive higher-order sliding mode observer (AHOSMO) based synchronous state and speed estimation method for linear induction motors is proposed to address the shortcomings of traditional estimation methods in terms of accuracy and robustness. Considering the boundary effect of linear induction motors, a higher-precision mathematical model is established. Based on the above model, the proposed observer combines the adaptive law and the higher-order sliding mode method to estimate the rotor fluxes and LIM speed, as well as the speed-dependent parameters <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\gamma, \alpha, \beta, \varsigma, \eta, \delta$</tex-math></inline-formula>. The application of a super-twisting algorithm (STA) guarantees finite-time convergence for LIM state variable estimation. By employing the higher-order sliding mode algorithm, continuous inputs can be generated without the chattering phenomenon. Numerical simulation and experimental results show that the proposed AHOSMO can quickly and accurately estimate the synchronous state and velocity of the LIM under different operating conditions. Compared with existing methods, the AHOSMO demonstrates significant advantages in estimation accuracy and anti-interference capability. The research results provide a new technical approach for higher-performance control of linear induction motors, which is of great significance for promoting their application in the field of high-precision positioning.
Keywords:
Linear induction motor
high order sliding mode observer
adaptive tuning law
super twisting algorithm
robustness
dynamic end effects
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