2015 - Ampère Prize (Prix Ampère de l’Électricité de France), French Academy of Sciences
His primary areas of investigation include Control theory, Nonlinear system, Differential algebra, Linear system and Applied mathematics. His Control theory study frequently draws connections between adjacent fields such as Control engineering. His Nonlinear system research is multidisciplinary, incorporating perspectives in Observability, Pure mathematics and Topology.
Michel Fliess interconnects Algorithm and Identifiability in the investigation of issues within Differential algebra. His Linear system study integrates concerns from other disciplines, such as PID controller, Robustness and Operational calculus. His Applied mathematics study incorporates themes from Mathematical analysis, Differential, Constant, Formal power series and Algebraic differential equation.
His primary scientific interests are in Control theory, Nonlinear system, Control engineering, Algebraic number and Applied mathematics. His study in Robustness, Flatness, PID controller, Linear system and Nonlinear control is done as part of Control theory. Michel Fliess combines subjects such as Controllability, Differential algebra and Differential equation with his study of Nonlinear system.
Michel Fliess works mostly in the field of Differential algebra, limiting it down to concerns involving Operational calculus and, occasionally, Noncommutative ring. His Control engineering research includes themes of Numerical differentiation, Control, Identification and Model free. His Applied mathematics research incorporates elements of Simple, Mathematical analysis and Optimal control.
His scientific interests lie mostly in Control theory, Model free, Control engineering, Control and Robustness. Michel Fliess studies Control theory which is a part of Control theory. The concepts of his Model free study are interwoven with issues in Calibration, Simple, Automotive engineering and Control algorithm.
His study in Control is interdisciplinary in nature, drawing from both Control system, Feedback loop, Simulation and Time series. His studies in Control system integrate themes in fields like Term, Order and Inventory control, Operations research. Michel Fliess works mostly in the field of Robustness, limiting it down to topics relating to Torque and, in certain cases, Nonlinear system and MATLAB, as a part of the same area of interest.
The scientist’s investigation covers issues in Model free, Control theory, Control engineering, Control and Calibration. The various areas that Michel Fliess examines in his Model free study include Intelligent control, Automotive engineering and Voltage. He combines subjects such as Phase and Aerodynamics with his study of Control theory.
The concepts of his Control engineering study are interwoven with issues in Feedback loop and Computer experiment. The Control study combines topics in areas such as Term, Order and Operations research, Inventory control. His Calibration research is multidisciplinary, incorporating elements of Simple, Feature and Model predictive control.
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Flatness and defect of non-linear systems: introductory theory and examples
Michel Fliess;Jean Lévine;Philippe Martin;Pierre Rouchon.
International Journal of Control (1995)
A Lie-Backlund approach to equivalence and flatness of nonlinear systems
M. Fliess;J. Levine;P. Martin;P. Rouchon.
IEEE Transactions on Automatic Control (1999)
An algebraic framework for linear identification
Michel Fliess;Michel Fliess;Hebertt Sira–Ramírez.
ESAIM: Control, Optimisation and Calculus of Variations (2003)
Generalized controller canonical form for linear and nonlinear dynamics
M. Fliess.
IEEE Transactions on Automatic Control (1990)
Fonctionnelles causales non linéaires et indéterminées non commutatives
Michel Fliess.
Bulletin de la Société Mathématique de France (1981)
Model-free control
Michel Fliess;Cédric Join.
International Journal of Control (2013)
Nonlinear observability, identifiability, and persistent trajectories
S. Diop;M. Fliess.
conference on decision and control (1991)
Sur les systèmes non linéaires différentiellement plats
M. Fliess;J. Levine;P. Martin;P. Rouchon.
Comptes rendus de l'Académie des sciences. Série 1, Mathématique (1992)
Non-linear estimation is easy
Michel Fliess;Cédric Join;Hebertt Sira-Ramirez.
International Journal of Modelling, Identification and Control (2008)
Numerical differentiation with annihilators in noisy environment
Mamadou Mboup;Mamadou Mboup;Cédric Join;Cédric Join;Michel Fliess;Michel Fliess.
Numerical Algorithms (2009)
Profile was last updated on December 6th, 2021.
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French Institute for Research in Computer Science and Automation - INRIA
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Publications: 34
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