Encoderless Parallel Predictive Torque Control for Induction Machine Using A Robust Model Reference Adaptive System

Haotian Xie, Fengxiang Wang, Yingjie He, Jose Rodriguez, Ralph Kennel

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


This paper proposes a robust model reference adaptive system (MRAS) estimator incorporating online parameter identification algorithm for parallel predictive torque control (PPTC) scheme. In contrast to conventional predictive torque control (PTC), the proposed PPTC is designed to facilitate the determination of weighting factor that modifies the relative importance of the control objectives, by simultaneously evaluating the torque and flux tracking error terms. The weighting factor is fine-tuned via an adaptive selecting mechanism, to obtain the attractive feature of reduced torque and current tracking errors. Besides, an encoderless MRAS-based estimator is employed for rotor speed and stator flux estimation to reduce the hardware complexity. However, this proposed encoderless PPTC algorithm still suffers from weak robustness against inevitable disturbances caused by parameter variations, which is an important issue to be further investigated. In this paper, an encoderless MRAS estimator combined with online parameter identification algorithm is proposed as an effective solution to accurately estimate the rotor speed and predicted stator flux-linkage, that improves robustness against mismatched parameters for the proposed encoderless PPTC scheme. The feasibility of the proposed algorithm is verified through the obtained experimental measurements, that achieves precise speed tracking capability as well as reduced torque and current tracking errors.

Original languageEnglish
JournalIEEE Transactions on Energy Conversion
Publication statusAccepted/In press - 2021


  • model reference adaptive system (MRAS)
  • online parameter identification
  • optimal weighting factor
  • parallel predictive torque control
  • Prediction algorithms
  • Predictive models
  • Robustness
  • Rotors
  • Stators
  • Torque
  • Torque control

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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