Time-varying state observer based twisting control of linear induction motor considering dynamic end effects with...

Area of Science:

• Electrical Engineering
• Control Systems
• Robotics

Background:

• Linear induction motors (LIMs) are crucial in various industrial applications.
• Accurate control of LIMs is challenging due to dynamic end effects and uncertainties.
• Existing control methods often struggle with finite-time convergence and disturbance rejection.

Purpose of the Study:

• To develop a robust time-varying state observer based twisting control (TC) scheme for LIMs.
• To address dynamic end effects and improve speed and flux tracking performance.
• To enhance the estimation of critical motor parameters like speed derivative and load torque.

Main Methods:

• Utilized Ducan's T-model and indirect field oriented control for LIM state space representation.
• Developed a time-varying state observer for rotor flux estimation, proving stability via Lyapunov's theory.
• Applied a twisting algorithm (TA) to extended flux and speed subsystems for finite-time convergence.
• Implemented a second-order sliding mode observer for speed derivative estimation and a reduced-order observer for load torque estimation.

Main Results:

• Achieved finite-time convergence for speed and flux tracking in the presence of disturbances and uncertainties.
• Successfully estimated rotor flux, speed derivative, and load torque with high accuracy.
• Demonstrated the effectiveness and feasibility of the proposed TC scheme through Hardware-in-the-Loop (HIL) experiments.

Conclusions:

• The proposed time-varying state observer based TC scheme offers a robust and effective solution for LIM control.
• The method significantly improves tracking performance and parameter estimation accuracy.
• Validated results confirm the practical applicability of the developed control strategy in real-world scenarios.