Online Seminar Series for IFAC TC 1.2 Adaptive & Learning Systems

The main objectives of our "Online Seminar Series for IFAC TC 1.2 Adaptive & Learning Systems" are:

• Promote the latest research results in the field of Adaptive and Learning Systems;
• Create a forum for high-quality discussion of both theoretical and practical perspectives;
• Reach and engage the researchers and practitioners in our community worldwide;
• Provide a platform for the young generation to network with the rest of the world.


Organization of the Seminar Series:

We plan to run the online seminar series on a monthly basis. We will invite speakers at different career stages, both within and outside of the TC, to share their research with the community. To encourage and train the young generation, e.g., PhD students. We will also organise special events within the seminars series to provide a venue for them to share and discuss their research with their peers and experts in the community.

The seminar will be open to all researchers and practitioners across the world. It will be scheduled at a suitable time (in the afternoon, UTC time) to maximise the possible attendance. The lectures will be recorded and hosted on IFAC YouTube Channel (upon the permissions of the speakers and approval of IFAC).

Details of Next Seminar: 

The next webinar in this series will be given by Professor Eric Rogers, University of Southampton, UK.

Title: Iterative Learning and Repetitive Control — A Status Report
Time: November 26, 2025 (03:00pm GMT)

Abstract: Iterative learning control (ILC) applies to systems that repeatedly perform the same finite-duration task. A particular example is a gantry robot executing a pick-and-place task, where the sequence of operation is i) collect the payload from a specified position, ii) transfer it over a finite duration, iii) place the payload at a specified location or onto a moving conveyor under synchronization, iv) return to the starting location, and v) repeat i)-iv) as many times as required or until a stop for, e.g., maintenance is required. Once an execution is complete, all generated information is available for potential use in updating the control input for the subsequent execution, which is computed when the robot returns to its starting location. The resetting action is not necessary for the application of ILC; it is enough that there is a stoppage time between one execution and the start of the next. Consequently, ILC can be applied to batch processing. The basic control setup involves specifying a reference signal to represent the ideal response on each execution. Then the design problem can be formulated as minimizing the sequence whose entries are the errors between the reference and the output on the corresponding execution number. Repetitive Control (RC) has been developed for applications where the reference trajectory is periodic and there is no stoppage time between successive executions. Although there is some evidence to the contrary, research on ILC and RC began in earnest in the mid-to-late 1980s. Since then, many approaches to design have been developed for both linear and nonlinear dynamics. This presentation will focus on the development of algorithms that have been followed through to experimental testing and application. Some ideas for possible future research will also be discussed.

To join the seminar, you may use the meeting link below:

Join Teams Meeting
https://msteams.link/MV3G
Meeting ID: 357 608 426 173 84
Passcode: VF6Zy6Fm

We will open the meeting 15 minutes earlier. The participants must join earlier - 10 minutes before the start. It will take some time to let them all in :-)

All of you are welcome! See you there!

Tiago Roux Oliveira (Chair of the TC 1.2: Adaptive and Learning Systems)
Bing Chu  (Vice-Chair for Social Media of the TC 1.2: Adaptive and Learning Systems)

Past Webinars:

  • Professor Warren Dixon from University of Florida, USA.
    • Title: Real-time Lyapunov-based deep learning for autonomous systems
    • Time: November 10, 2025 (12:00pm EST)
    • Video: TBC
  • Professor Anders Rantzer from Lund University (LTH), Sweden.
  • Professor Alexander Fradkov from SPbU, Russia.
    • Title: Speed-Gradient for Modeling, Control, Adaptation and Learning
    • Time: October 08, 2025 (02:00pm UTC)
    • Video: https://youtu.be/bt4_nqaJL4k
  • Professor Florian Dörfler from ETH Zurich.
  • Professor Anuradha Annaswamy from MIT, USA.
  • Professor Romeo Ortega, Instituto Tecnológico Autónomo de México.
    • Title: New Robust Parameter Estimators and Systems Reparameterizations: Dealing with Lack of Excitation and Nonlinear Parameterizations
    • Time: September 26, 2023 (11am CDT, 4pm UTC)
    • Video: https://youtu.be/N3qfiakYsCI 
  • Professor Denis Dochain, Université catholique de Louvain.
    • Title: Automatic Control and Biological Systems: a long quiet river?
    • Time: April 12, 2023 (9am CDT, 2pm UTC) 
    • Video: https://youtu.be/VZ5y7HckfeM
  • Professor Na Li, Harvard University, Cambridge.
    • Title: Scalable Distributed Control and Learning of Networked Dynamical Systems
    • Time: February 15, 2023 (7am PST, 9am CDT, 3pm UTC) 
    • Video: https://youtu.be/sGOzBUWTcBk
  • Professor Magnus Egerstedt, University of California, Irvine.
    • Title: Constraint-Based Control Design for Assured and Long-Duration Autonomy
    • Time: January 11, 2023 (9am PST, 11am CDT, 5pm UTC)
    • Video: https://youtu.be/ATqcna2YoDg 
  • Professor John Ringwood, Maynooth University. 
    • Title: Energy maximising control for wave energy systems: an extremum seeking problem?
    • Time: December 19, 2022 (4pm UTC)
    • Video: https://youtu.be/vQCyfawXVog 
  • Professor Martin Guay, Queen’s University. 
    • Title: Data driven control of unknown nonlinear systems using extremum seeking control
    • Time: May 27, 2022 (8am PST, 10am CDT, 3pm UTC)
    • Video: https://youtu.be/MMr8M9JpGD8
  • Professor Tamer Basar, University of Illinois Urbana-Champaign.
    • Title: Policy Optimization for Optimal Control with Guarantees of Robustness
    • Time: April 27, 2022 (8am PST, 10am CDT, 3pm UTC)
    • Video: https://youtu.be/7sjv24wNyBA
  • Professor Miroslav Krstic, University of California, San Diego.
    • Title: The Magical Worlds of Adaptive Stabilization and Optimization
    • Time: March 14, 2022 (8am Pacific Daylight Time, 3pm Universal Time UTC)
    • Video: https://youtu.be/X_N-0N22VZE

https://tc.ifac-control.org/1/2