Seminars

2021

  • V.R. Rajagopal, K.R. Ramaswamy and P.M.J. Van den Hof (2021). Learning local modules in dynamic networks without prior topology information. 60th IEEE Conf. Decision and Control, December 13-15, 2021, Austin, TX, USA. slides video
  • T.R.V. Steentjes, M. Lazar and P.M.J. Van den Hof (2021). H_infinity performance analysis and distributed controller synthesis for interconnected linear systems from noisy input-state data. 60th IEEE Conf. Decision and Control, December 13-15, 2021, Austin, TX, USA.  slides  video
  • T.R.V. Steentjes, P.M.J. Van den Hof and M. Lazar (2021). Handling unmeasured disturbances in data-driven distributed control with virtual reference feedback tuning. 19th IFAC Symposium on System Identification – Learning Models for Decision and Control, July 14-16, 2021, Padova, Italy.  slides  video
  • H.J. Dreef, M.C.F. Donkers and P.M.J. Van den Hof (2021). Identifiability of linear dynamic networks through switching modules. 19th IFAC Symposium on System Identification – Learning Models for Decision and Control, July 14-16, 2021, Padova, Italy.  slides  video
  • S. Shi, X. Cheng and P.M.J. Van den Hof. Exploiting non-measured disturbance signals in identifiability of linear dynamic networks with partial measurement and partial excitation. 19th IFAC Symposium on System Identification – Learning Models for Decision and Control, July 14-16, 2021, Padova, Italy.  slides  video
  • Invited tutorial session on “Data-driven modeling in dynamic networks”, 2021 European Control Conference, 30 June 2021, 15:30-17:30.
    • Paul Van den Hof: Introduction. slides  video
    • Xiaodong Cheng: Graph-theoretical methods for identifiability analyis and synthesis in dynamic networks. slides  video
    • Arne Dankers: Leak detection in pipelines using acoustic sensors and system identification. video
    • Karthik R. Ramaswamy: Single module identification in dynamic networks. video
  • T.R.V. Steentjes, M. Lazar and P.M.J. Van den Hof. Data-driven distributed controller synthesis in the presence of noise: an optimal controller identification approach. 2021 European Control Conference, ECC 2021, June 29 – July 2, 2021, Rotterdam, The Netherlands. slides  video 
  • X. Cheng, S. Shi and P.M.J. Van den Hof. Identifiability in dynamic acyclic networks with partial excitation and measurement.  2021 European Control Conference, ECC 2021, June 29 – July 2, 2021, Rotterdam, The Netherlands. slides  video 
  • S. Fonken, K. Ramaswamy and P.M.J. Van den Hof. Multi-step scalable least-squares method for network identification with unknown disturbance topology. 40th Benelux Meeting on Systems and Control, Rotterdam, The Netherlands, 29 June 2021.  slides
  • P.M.J. Van den Hof and K.R. Ramaswamy.  Learning local modules in dynamic networks. 3rd Annual for Dynamics and Control Conference, June 7-8, 2021, ETH Zurich, Switzerland. slides  video

2020

  • T.R.V. Steentjes, M. Lazar and P.M.J. Van den Hof.  Data-driven distributed control via virtual reference feedback tuning. 59th IEEE Conf. Decision and Control, Jeju Island, Republic of Korea, 15-18 December 2020. slides  video
  • P.M.J. Van den Hof and K.R. Ramaswamy. Path-based data-informativity conditions for single module identification in dynamic networks. 59th IEEE Conf. Decision and Control, Jeju Island, Republic of Korea, 15-18 December 2020. slides  video
  • V.C. Rajagopal, K.R. Ramaswamy and P.M.J. Van den Hof. A regularized kernel-based method for learning a module in a dynamic network with correlated noise. 59th IEEE Conf. Decision and Control, Jeju Island, Republic of Korea, 15-18 December 2020. slides  video
  • P.M.J. Van den Hof and K.R. Ramaswamy. Single module identification in dynamic networks – the current status. Survey presentation in Open Invited Track, “Data-driven modeling and learning in dynamic networks”, 21st IFAC World Congress, Berlin, Germany, 12-17 July 2020. slides  video
  • S. Shi, X. Cheng and P.M.J. Van den Hof. Excitation allocation for generic identifiability of a single module in dynamic networks: A graphic approach. 21st IFAC World Congress, 12-17 July 2020, Berlin, Germany. slides  video
  • P.M.J. Van den Hof. Data-driven model learning in linear dynamic networks. Plenary lecture, 39th Benelux Meeting on Systems and Control, Elspeet, The Netherlands, 11 March 2020. slides
  • P.M.J. Van den Hof. Data-driven model learning in linear dynamic networks. Invited plenary lecture, 6th International Conference on Advances in Control & Optimization of Dynamical Systems, IIT Madras, Chennai, India, 17 February 2020. slides

2019

  • P.M.J. Van den Hof. Data-driven model learning in linear dynamic networks. Coordinated Science Lab, University of Illinois, IL, USA, 19 November 2019. slides
  • P.M.J. Van den Hof. Data-driven modeling in linear dynamic networks – Identifiability. Japan Automatic Control Conference, Sapporo, Japan, 10 November 2019. slides
  • P.M.J. Van den Hof. Data-driven modelling in linear dynamic networks. 10th Harry Nicholson Distinguished Lecture in Control Engineering, The University of Sheffield, UK, 21 May 2019. slides
  • P.M.J. Van den Hof. Data-driven modelling in linear dynamic networks. IFAC Lecture, Vienna, Austria, 4 April 2019. slides
  • P.M.J. Van den Hof. Local module identification in dynamic networks with correlated noise.  Seminar, RU Groningen, 25 February 2019. slides

2018

  • P.M.J. Van den Hof. Data-driven modelling in linear dynamic networks. Seminar, Control and Dynamical Systems, California Institute of Technology, Los Angeles, CA, USA, 7 December 2018. slides
  • P.M.J. Van den Hof. Data-driven modelling in linear dynamic networks. Seminar, Department of Mechanical and Aerospace Engineering, University of California at San Diego, CA, USA, 30 November 2018. slides
  • P.M.J. Van den Hof. Data-driven modelling in linear dynamic networks. Plenary address, 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys18), 28 August 2018, Groningen, The Netherlands. slides
  • P.M.J. Van den Hof. Data-driven modelling in linear dynamic networks. Plenary address, 18th IFAC Symposium on System Identification, 10 July, 2018, Stockholm, Sweden. slides

2017

  • P.M.J. Van den Hof. Identification of linear dynamic networks with rank-reduced noise. CARMA Workshop on Mathematical Systems Theory and Applications. University of Newcastle, NSW, Australia, 7 December 2017. slides
  • P.M.J. Van den Hof. Data-driven modeling in linear dynamic  networks. School of Electrical Engineering and Computing, University of Newcastle, NSW, Australia, 5 December 2017.  slides
  • P.M.J. Van den Hof. Identification in dynamic networks. FOCAPO/CPC 2017, invited paper, Tucson, AZ, 10 January 2017 and University of Houston, TX, 13 January 2017. slides

2016

  • P.M.J. Van den Hof. Identifiability of dynamic netwoks with noisy and noise-free nodes. TU Vienna, Department of Econometrics and System Theory, 21 November 2016. slides
  • P.M.J. Van den Hof, H.H.M. Weerts and A.G. Dankers. Identifiability of dynamic netwoks with noisy and noise-free nodes. ERNSI Workshop, Cison di Valmarino, Italy, 24-27 September 2016.  slides
  • P.M.J. Van den Hof. System identification in dynamic networks. University of Oxford, UK, 14 June 2016. slides