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Fethi Bencherki

About me

PhD Student at the Department of Automatic Control since Aug 2021. Supervised by Anders Ranzter. I have a MSc in Control Systems where I did my thesis on state-space identification of switched systems. The interested reader can find it here.


Fall 2021

  • FRTN05 - Non-Linear Control and Servo Systems

Spring 2022

  • FRTF05 - Automatic control, basic course for FIPi

Fall 2022

  • FRTF05 - Automatic Control, Basic Course for DE
  • FRTN05 - Non-Linear Control and Servo Systems

Fall 2023

  • FRTF05 - Automatic Control, Basic Course for DE
  • FRTN05 - Non-Linear Control and Servo Systems

Research and Publications

I am within the NEST project and my research interest revolves around developing scalable control approaches for large scale networks. I am also interested in learning-based control and the identification of switched systems. Below is a list of publications and preprints.

Ongoing work

Learning optimal dispatching policies over queueing networks, to appear soon as a preprint


Observer based switched-linear system identification, submitted to IEEE Transactions on Automatic Control

MIMO switched-linear system identification from input-output data, submitted to International Journal of Robust and Nonlinear Control



MIMO-SLS identification from input-output data, in 18th IEEE International Conference on Control & Automation (ICCA 2024)

Realization of MIMO-SLSs from Markov parameters via forward/backward corrections, in European Control Conference (ECC 2024)

Robust simultaneous stabilization via minimax adaptive control, in 62nd IEEE Conference on Decision and Control (CDC 2023)

Basis transform in switched linear system state-space models from input-output data, in International Journal of Adaptive Control and Signal Processing

Realization of multi-input/multi-output switched linear systems from Markov parameters, in Nonlinear Analysis: Hybrid Systems

Achieving consensus in networks of increasingly stubborn voters, in 61st IEEE Conference on Decision and Control (CDC 2022)



Google scholar

LU research portal profile




Postal address:
Box 118, SE-221 00 Lund, Sweden

Visiting address:
M-huset, 2147
floor 2