Jingli Huang

Mrs. Jingli Huang


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 June 2025 in Actuators
Verified
Journal Article
Open access
PDF file
ZLZHANG LEI
ZHANG LEI
XXXiaodong Xie
Xiaodong Xie
DWDabiao Wu
Dabiao Wu
ZWZicheng Wang
Zicheng Wang
建王建立 王
建立 王
JHJingli Huang
Jingli Huang
This paper presents a novel adaptive twisting sliding mode control strategy combined with a speed-sensorless cascade nonlinear observer for the high-performance control of linear induction motors (LIMs). The primary objective is to achieve accurate speed and rotor flux tracking without relying on mechanical sensors, thereby enhancing system reliability and reducing hardware complexity. For this purpose, a cascade nonlinear observer is designed and applied to the class of nonlinear affine systems representing LIM dynamics. Based on the interconnected form of the LIM mathematical model, the observer simultaneously reconstructs both the motor speed and rotor fluxes in real time. The stability of the proposed cascade observer is analyzed using Lyapunov theory, ensuring the convergence of the estimation errors under bounded disturbances. Complementing the observer, two adaptive gain twisting sliding mode controllers are developed: one for speed tracking and another for flux regulation. These controllers are robust against external disturbances and parameter uncertainties, even when the bounds of such disturbances are unknown. This feature significantly enhances the practical applicability of the control system in real-world industrial environments. To validate the performance and robustness of the proposed control scheme, a hardware-in-the-loop (HIL) experiment was conducted. Comparative studies with existing state-of-the-art sensorless control methods demonstrate that the proposed cascade nonlinear observer-based approach achieves faster convergence, higher estimation accuracy, and better disturbance rejection capabilities, while requiring less computational effort.