

The workshop and tutorial sessions at ICFDA 2024 will take place on Monday, July 8 and Tuesday, July 9, 2024.
The ICFDA 2024 will offer halfday, fullday, or twoday workshops and tutorials. Organizers are invited to prepare proposals with a clear focus on new and emerging topics within the general scope of automatic control. It is desirable that the workshops and tutorials are interactive, creating an engaging atmosphere for the participants. The organizers are also asked to make the events diverse and inclusive for people with different backgrounds and expertise.
The proposals for tutorials and workshops should be concise and must be limited to 6 pages in PDF format. There is no specific template but it should include the following items:
Additional points:
Submission of workshop/tutorial proposals should be made using the ifac.papercept.net site. Detailed information can be found in the submission procedure page.
Proposers: YangQuan Chen
Halfday proposal (Tuesday afternoon– July 9)
Fractional order calculus is about differentiation and integration of noninteger orders. Fractional calculus based fractional order thinking (FOT) has been shown to help us to better understand complex systems, better process complex signals, better control complex systems, better perform optimizations, and even better enable creativity. In this tutorial, we will briefly talk on basics of fractional calculus, fractional order thinking, and its rich stochastic models. Then we will justify why fractional calculus is needed in machine learning when we ask “what is the more optimal way to optimize?”. We will also ask why fractional calculus is needed in data when we ask “how to quantify variability and the complexity of the systems that generate the big data?” We will share rich future research opportunities and a new forum to publish the related results.
Proposers: Sergei Levendorskii
Fullday proposal (Tuesday – July 9)
FourierLaplace transform technique allows one to represent several classes of important probability distributions and solutions of basic boundary problems for wide classes of fractional ddifferential equations as integrals of functions enjoying two key properties: analytic continuation to a cone or the union of a cone and tube domain, and regular decay at infinity. Integral representations for WienerHopf factors, fractional moments and special functions enjoy these properties as well. In the tutorial, we present the general methodology which allows one to evaluate the integrals enjoying these properties very fast and accurately. Among applications, we derive new efficient realizations of the Fourier, Laplace and Ztransforms, representations for probability distributions in Levy models, stable ones including, and algorithms for pricing contingent claims, MonteCarlo simulations, evaluation of special functions and filtering of highly persistent shocks.
Proposers: Stéphane Victor and Rachid Malti
Fullday proposal (Tuesday – July 9)
Fractional (or noninteger) differentiation has played an important role in various fields notably in signal and image processing and control theory. In these last fields, important considerations such as modeling, system identification and observability are now linked to longrange dependence phenomena. It is expected that such an open invited track attracts new researchers and developers that use fractional calculus in the areas of mathematics, physics, engineering and particularly in automatic control. The latest developments for continuoustime modeling and system identification with fractional order models are proposed in the newest CRONE toolbox (version 2.0). Fully compatible with the latest Matlab® versions (since 2020a), it includes timedomain identification algorithms for estimating continuoustime models. Thanks to this new programming, the options arguments of the proposed functions have been simplified and updated. In order to help a new user, a tutorial has been completely revised as the CRONE demos command which allows handling the new options. A Guided User Interface (GUI) is now available, as the CroneIdentification application so that a user, familiar with the Matlab SystemIdentification GUI, can easily handle the system identification methods for preprocessing data, defining a model structure and estimating as well the coefficients as the differentiation orders.
This tutorial prepares the audience with:
1. System modeling with the different classes (frac_poly_exp, frac_tf, frac_lti…)
2. Simulation of fractional order models
3. System Identification with fractional order model: coefficient and order estimations
4. CroneIdentification application
Proposers: Blas M. Vinagre
Halfday proposal (Tuesday morning– July 9)
In this course we will study the mathematical foundations, the historical development and the applications of Fractional Calculus in science and enginee ring, with a special emphasis on the applications in feedback control, robotics and bioengineering, related disciplines in the framework of cybernetics.
Proposers: Patrick Lanusse
Fullday proposal (Tuesday – July 9)
Fractional (or noninteger) differentiation has played an important role in various fields notably in signal and image processing and control theory. In control theory, fractional order differentiation provides very high powerful degrees of freedom which simplify the design of high performance feedback controllers. very powerful degrees of freedom that simplify the design of highperformance feedback controllers. The CRONE Control System Design (CSD) methodology proposes to design robust controllers using real or complex fractional order operators. A toolbox fully compatible with the latest versions of Matlab® has been developed based on this methodology and is available free of charge to the international scientific and industrial communities. For systems with uncertain/perturbed models, with 3 generations of the CRONE CSD methodology, this toolbox allows the design in the frequency domain of continuoustime or discretetime SISO controllers but also of decentralized MIMO controllers.
This tutorial prepares the audience with:
1. defining the uncertain model of plants and their control requirements
2. the choice of CRONE CSD methodology generation to use
3. robust controller design
4. CRONE controller evaluation with Simulink toolbox
Online user: 2  Privacy 