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PROF Michael Cantoni

Positions

  • Automation of water distribution networks
  • Control and signal processing

Overview

OverviewText1

  • Michael Cantoni is full Professor in the Department of Electrical and Electronic Engineering and Head of the Control and Signal Processing Group. He received the Bachelor of Engineering (Electrical - Hons. 1) and Bachelor of Science (Applied Mathematics) degrees from The University of Western Australia in 1995, and the PhD degree in Engineering from The University of Cambridge in 1998. Before joining The University of Melbourne in 2000, he held post-doctoral research positions with Department of Engineering at The University of Cambridge, and St. John's College, Cambridge. He has served as associate editor for IET Control Theory and Applications (2007–2010), Systems & Control Letters (2007–2014), and IFAC Automatica (2015-2018). In 2014, he was co-recipient of the IEEE CSS Control Systems Technology Award for work with industry partner Rubicon Water on the automation of rural distribution networks. His research interests include robust and optimal control theory, distributed control and optimization of networks, time-varying and sampled-data systems, model approximation, multidimensional systems, and applications in water and power distribution.   

Affiliation

Member of

  • IEEE - Institute of Electrical and Electronic Engineers (USA). Member 1994 -

Publications

Selected publications

Research

Investigator on

Awards

Education and training

  • PhD, University of Cambridge 1998
  • BEng (Hons), The University of Western Australia 1995
  • BSc, The University of Western Australia 1995

Awards and honors

  • Control System Technology Award, IEEE Control System Society, 2014
  • Knowledge Transfer Award, The University of Melbourne, 2007

Linkages

Supervision

Available for supervision

  • Y

Supervision Statement

  • Research interests:
    - Robust and optimal control
    - Distributed control and optimization of networks
    - Time-varying and sampled-data systems
    - Model approximation
    - Multidimensional systems
    - Applications in water and power distribution