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A sensorless control using a sliding-mode observer for an electromagnetic valve actuator in automotive applications

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Authors

In this paper, based on a non-linear model, a particular sliding mode observer is presented. Considerations on constructive aspects concerning observability is made. Control strategy is presented and discussed as well. Both computer simulation and laboratory experimental of the controlled system are presented which demonstrate promising behavior.
Original languageEnglish
Title of host publication6th IET International Conference on Power Electronics, Machines and Drives, PEMD 2012
Number of pages6
PublisherThe Institution of Engineering and Technology
Publication date03.2012
Article numberB64
ISBN (print)9781849196161
ISBN (electronic)978-184919616-1
DOIs
Publication statusPublished - 03.2012
Event6th IET International Conference on Power Electronics, Machines and Drives - PEMD 2012 - University of Bristol , Bristol, United Kingdom
Duration: 27.03.2012 → 29.03.2012
Conference number: 6
https://digital-library.theiet.org/content/conferences/cp592

    Research areas

  • Actuators, Lyapunov methods, Nonlinear observers, Sensorless control, Automotive applications, Control strategies, Controlled system, Electromagnetic valves, Non-linear model, Non-linear observer, Sensor less control, Sliding mode observers, Sliding-mode observer, Computer simulation, Power electronics
  • Engineering

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Research output: Journal contributions › Journal articles › Research › peer-review

Automatic Tuning of Extended Kalman Filter in Synchronous Reluctance Motor Drives with a Master-Slave Configuration

Rigon, S., Haus, B., Mercorelli, P. & Zigliotto, M., 27.02.2025, (E-pub ahead of print) In: IEEE Open Journal of Power Electronics. 14 p.

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Dynamic Performance Analysis and Fault Ride-Through Enhancement by a Modified Fault Current Protection Scheme of a Grid-Connected Doubly Fed Induction Generator

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Zwerger, T. & Mercorelli, P., 01.02.2025, In: Mathematics and Computers in Simulation. 228, p. 178-201 24 p.

Research output: Journal contributions › Journal articles › Research › peer-review

Neural Network-Based Finite-Time Control for Stochastic Nonlinear Systems with Input Dead-Zone and Saturation

Kharrat, M., Krichen, M., Alhazmi, H. & Mercorelli, P., 11.01.2025, (E-pub ahead of print) In: Arabian Journal for Science and Engineering. 11 p.

Research output: Journal contributions › Journal articles › Research › peer-review

DOI

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