Iterative learning control of vessel propulsion system based on tethered kite

Le stage aura lieu au laboratoire IMS, qui est une unité mixte de recherche (UMR) entre l'Université de Bordeaux, le Bordeaux INP et le CNRS.

As part of the KiWin project, involving three academic partners and Beyond the Sea (BTS) company (based in Arcachon, France), the IMS-laboratory (University of Bordeaux, Bordeaux INP, CNRS) is working on control and supervision algorithms design of tethered kites for vessel propulsion. Multiple version of these kites have been developed by BTS, starting from a beach kite of 5m² and going up to 800m² for large vessel propulsion. An estimated 20% reduction in fuel consumption of the vessel is
expected, providing great benefits for maritime transportation and environment preservation.

This internship will mostly focus on a 5m² kite version, that is not onboard the boat but on the beach. As such, it is better adapted for initial experimental evaluation of control and supervision algorithms. Robust control and supervision algorithms have been developed and evaluated [3, 5, 6]. The scope of this internship is to assess more advanced adaptive control algorithms for the kite and compare with existing robust control methods based on the CRONE methodology [7]. The focus will be in particular on Iterative Learning Control (ILC) algorithms. An initial list of bibliography items on this topic is given [1, 2, 4]. It is expected that the recruited internship student will propose and analyse
in simulation an ILC algorithm for kite control before the end of the internship. The ILC algorithm is expected to optimize the control and the trajectory to maximise the traction force produced by the kite.

The main tasks of this internship are:
1. Based on existing work in the IMS-lab and available literature, understand the dynamic modelling of the kite and design a simulator (preferably in Matlab, Julia or Python can be accepted as well). Additionally, varying atmospheric conditions, tether elasticity and boat oscillations should be introduced to improve its realism.
2. Design robust feedback CRONE controller based on existing works and validate it on the simulator. Linearization based on designed simulator is necessary.
3. In depth literature review on ILC algorithms, starting with the initial references list: [1, 2, 4].
4. Propose a new ILC algorithm, providing theoretical analysis based on literature.

5. Evaluate in simulation the proposed algorithm in various conditions.
6. Write a conference paper to present the proposed algorithm.
7. Internship manuscript should be updated continuously and adjusted as per the supervisors’ comments.

References
[1]Leontine Aarnoudse, Johan Kon, Koen Classens, Max Van Meer, Maurice Poot, Paul Tacx, Nard
Strijbosch, and Tom Oomen. “Cross-Coupled Iterative Learning Control for Complex Systems: A
Monotonically Convergent and Computationally Efficient Approach”. en. In: 2022 IEEE 61st Con-
ference on Decision and Control (CDC). Cancun, Mexico: IEEE, Dec. 2022, pp. 1485–1490.
[2]Katrin Baumgartner and Moritz Diehl. “Zero-Order Optimization-Based Iterative Learning Control”.
en. In: 2020 59th IEEE Conference on Decision and Control (CDC). Jeju, Korea (South): IEEE,
Dec. 2020, pp. 3751–3757.
[3]Baptiste Cadalen. “Modélisation et commande robuste d’une aile de kite en vol dynamique—application
à la traction d’un navire”. fr. PhD thesis. Université de Bordeaux, 2018.
[4]Mitchell Cobb, James Reed, Joshua Daniels, Ayaz Siddiqui, Max Wu, Hosam Fathy, Kira Barton,
and Chris Vermillion. “Iterative Learning-Based Path Optimization With Application to Marine
Hydrokinetic Energy Systems”. en. In: IEEE Transactions on Control Systems Technology 30.2 (Mar.
2022), pp. 639–653.
[5]Enso Ndreko, Monika Pasquali, Tudor-Bogdan Airimitoaie, Christophe Farges, and Patrick Lanusse.
“Rigid Body Modeling and Dynamic Flight Control of a Tethered Kite”. en. In: 2024 12th Interna-
tional Conference on Control, Mechatronics and Automation (ICCMA). London, United Kingdom:
IEEE, Nov. 2024, pp. 415–420.
[6]Monika Pasquali, Enso Ndreko, Tudor-Bogdan Airimitoaie, Christophe Farges, and Patrick Lanusse.
“Optimal flight trajectories of a tethered kite for ship propulsion under variable wind conditions”.
en. In: 2024 12th International Conference on Control, Mechatronics and Automation (ICCMA).
London, United Kingdom: IEEE, Nov. 2024, pp. 403–408.
[7]Jocelyn Sabatier, Patrick Lanusse, Pierre Melchior, and Alain Oustaloup. Fractional Order Differen-
tiation and Robust Control Design: CRONE, H-infinity and Motion Control. en. Vol. 77. Intelligent
Systems, Control and Automation: Science and Engineering. Dordrecht: Springer Netherlands, 2015.

Dynamic systems modelling and control, robust and adaptive control, and good coding skills in Matlab/Simulink are highly desired.