Professor Daniel Quevedo

Profile image of Professor Daniel Quevedo

Personal details

Keywords

Networked Systems, Systems and Control Theory, Cyberphysical systems, Cyberphysical Security, Control of Power Converters, Model Predictive Control

Research field

Applied mathematics, Electrical engineering

Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2020

Qualifications

  • PhD (University of Newcastle)

Professional memberships and associations


Teaching

During his tenure as head of the Automatic Control Chair at Paderborn University, Daniel was responsible for the design and implementation of the entire systems and control curriculum of the Faculty. He took this as an opportunity to modernise course contents and also teaching / learning methods in the BSc and MSc programmes offered. In particular, together with his group, he implemented innovative blended and practice-oriented learning concepts, including open-ending laboratory experiences. Courses offered include:

  • Regelungstechnik (Automatic Control)
  • Advanced Control
  • Advanced Systems Theory
  • Networked Estimation and Control
  • Topics in Automatic Control

In addition, Daniel has extensive experience with postgraduate student supervision and with coaching of early career academics. A selection of thesis topics is given below, followed by a list of his mentees.

Postgraduate Student Supervision (selection)

Doctorate

Masters (all as co-advisor whilst at Paderborn University)

  • "Learning and Optimization for Networked Control Systems" (2019)
  • "Generation of Simulation Scenarios for Autonomous Driving using Camera and Laser Data", in collaboration with dSPACE (2019)
  • "Control of an Inverted Pendulum using Reinforcement Learning" (2019)
  • "Control design for offshore wind turbine load reduction," in collaboration with ForWind - Centre for Wind Energy Research (2018)
  • "Control Methods for Platooning with Wireless Communications" (2018)
  • "Control in the presence of an eavesdropper" (2018)
  • "Robust non-linear model predictive control for mechatronic systems," in collaboration with IAV Automotive Engineering, Germany (2017)
  • "Investigation of estimation and control mechanisms for autonomous flight of a drone," in collaboration with Invensity GmbH, Germany (2017)
  • "Control of Sphero using computer vision and Raspberry Pi" (2016)

Supervision of Postdoctoral Fellows

  • Justin Kennedy, from QUT, since 2021
  • Jingyi Lu, from Hong Kong University of Science and Technology China, 2019-2021
  • Arun Ramaswamy, from Indian Institute of Science Bangalore, 2017-2020
  • Moritz Schulze Darup, from Ruhr University Bochum Germany, 2017-2020
  • Alex Leong, from University of Melbourne Australia, 2016-2019
  • Burak Demirel, from Royal Institute of Technology Sweden, 2015-2018
  • Daniel Dolz, from Universitat Jaume I Spain, 2016

Publications

  • Ding, K., Ren, X., Quevedo, D., Dey, S. & Shi, L. (2020). Defensive deception against reactive jamming attacks in remote state estimation. Automatica, 113, 1–11.
  • Leong, A., Ramaswamy, A., Quevedo, D., Karl, H. & Shi, L. (2020). Deep reinforcement learning for wireless sensor scheduling in cyber-physical systems. Automatica, 113, 1–8.
  • Schulze Darup, M., Redder, A. & Quevedo, D. (2019). Encrypted cooperative control based on structured feedback. IEEE Control Systems Letters, 3(1), 37–42.
  • Demirel, B., Leong, A., Gupta, V. & Quevedo, D. (2019). Tradeoffs in stochastic event-triggered control. IEEE Transactions on Automatic Control, 64(6), 2567–2574.
  • Leong, A., Quevedo, D. & Dey, S. (2018). Optimal Control of Energy Resources for State Estimation Over Wireless Channels. Springer.
  • Lopez, A., Quevedo, D., Aguilera, R., Geyer, T. & Oikonomou, N. (2018). Limitations and accuracy of a continuous reduced-order model for modular multilevel converters. IEEE Transactions on Power Electronics, 33(7), 6292–6303.
  • Mishra, P., Chatterjee, D. & Quevedo, D. (2018). Sparse and constrained stochastic predictive control for networked systems. Automatica, 87, 40–51.
  • Peters, E., Quevedo, D. & Fu, M. (2016). Controller and scheduler codesign for feedback control over IEEE 802.15.4 networks. IEEE Transactions on Control Systems Technology, 24(6), 2016–2030.
  • Nagahara, M., Quevedo, D. & Nesic, D. (2016). Maximum hands-off control: A paradigm of control effort minimization. IEEE Transactions on Automatic Control, 61(3), 735–747.
  • Aguilera, R. & Quevedo, D. (2015). Predictive control of power converters: Designs with guaranteed performance. IEEE Transactions on Industrial Informatics, 11(1), 53–63.

QUT ePrints

For more publications by Daniel, explore their research in QUT ePrints (our digital repository).

View more publications

Filter publications:

A complete list of publications is available at: https://www.qut.edu.au/about/our-people/academic-profiles/daniel.quevedo

Awards

Supervision

Completed supervisions (Masters by Research)

The supervisions listed above are only a selection.