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Fuzzy virtual reference model sensorless tracking control for linear induction motors.

Cheng-Yao Hung1, Peter Liu, Kuang-Yow Lian

  • 1LCD TV Business Unit,Wistron Corporation, Taipei, Taiwan.

IEEE Transactions on Cybernetics
|October 19, 2012
PubMed
Summary
This summary is machine-generated.

This study presents a novel fuzzy virtual reference model (FVRM) method for sensorless control of linear induction motors (LIMs). The approach simplifies speed tracking by converting it into a stabilization problem, ensuring robust performance.

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Area of Science:

  • Control Systems Engineering
  • Fuzzy Logic Applications
  • Electrical Machines

Background:

  • Sensorless control of linear induction motors (LIMs) is challenging due to the need for accurate speed estimation.
  • Existing methods often require complex models or additional sensors, increasing cost and reducing reliability.

Purpose of the Study:

  • To develop a novel fuzzy virtual reference model (FVRM) synthesis method for speed sensorless tracking control of LIMs.
  • To simplify the control design by transforming the speed tracking problem into a stabilization problem.
  • To unify the design of the controller and observer for improved performance and robustness.

Main Methods:

  • Representing the LIM using a Takagi-Sugeno fuzzy model.
  • Employing a fuzzy observer to estimate immeasurable states like mover speed and secondary flux.
  • Defining internal desired states using an FVRM to convert speed tracking into a stabilization problem.
  • Solving a set of linear matrix inequalities (LMIs) to obtain observer and control gains for guaranteed exponential convergence.

Main Results:

  • Successful estimation of LIM speed and flux without physical sensors.
  • Demonstration of speed tracking control converted into a stabilization problem.
  • Unified design of controller and observer through LMI formulation.
  • Experimental validation confirming satisfactory transient response and robustness.

Conclusions:

  • The proposed FVRM method offers a simplified and unified approach to speed sensorless control of LIMs.
  • The method eliminates the need for an actual reference model by generating internal desired states.
  • The LMI-based design guarantees exponential convergence and robust performance, validated through experiments.