Philippe Müllhaupt

Expertise Nonlinear Control (Geometry and Algebra)Classical DynamicsRoboticsStatistics Mission Provide rigorous technical and scientific training in nonlinear control, classical mechanics, and statistical theory Current Work Research and teaching in the fields of control theory, statistics, dynamical  systems, and general mechanics. Philippe Mullhaupt received his Diplôme d Education Ing�nieur | Electricit� 1993 – 1993 EPFL DEA | Automatique et Traitement du Signal 1994 – 1994 Paris-Sud Doctorat | Automatique 1999 – 1999 EPFL Professionals experiences Post-Doc 1999–2000 ENSMP-Paris (Fontainebleau)Researcher and Lecturer 2000–2014 EPFLScientist 2014–2016 EPFLScientist 2014–2017 EPFLScientist 2014–2018 EPFLResearcher and Lecturer 2014–2014 EPFLAcademic Promotion 2019–2025 EPFLInventory management and follow-ups 2017–2019 EPFL Teaching & PhD Past EPFL PhD Students as codirector Robert Fuchs, Davide Buccieri, Yvan Michellod, Willson Sudarsandhari Shibani, Basile Graf, David Ingram, Ehsan Sarshari Courses Discrete-time control of dynamical systems ME-324 An introduction to linear discrete-time control systems is provided which consists in applying a control at equally spaced time intervals. The consequence of the associated sampling process on the stability and performance of the closed-loop system is analysed in detail. Elements of statistics for data science EE-209 Estimation theory: maximum likelihood estimation, Fisher information.Cramer-Rao inequality. Confidence intervals.Hypotheses testing: Neyman-Pearson framework. Maximum likelihood test. Parametric and non parametric tests.Bayesian inference.Linear Models. General physics : mechanics PHYS-101(d) Give the student the basic notions that will allow him or her to have a better understanding of physical phenomena, such as the mechanic of point masses. Acquire the capacity to analyse quantitatively the consequences of these effects with appropriate theoretical tools. Introduction to control of dynamical systems ME-273 Introductory course on control of dynamical systems. Four key systems serve as the backbone to a unified abstract formalism. This formalism is then used to solve fundamental control problems such as tracking and disturbance rejection, with particular emphasis on guaranteeing closed-loop stability Linear system theory EE-611 The course covers control theory and design for linear time-invariant systems : (i) Mathematical descriptions of systems (ii) Multivariables realizations; (iii) Stability ; (iv) Controllability and Observability; (v) Minimal realizations and coprime fractions; (vi) Pole placement and model matching. Microinformatique (pour GM) ME-303 Understand Microcontrollers and learn to use them, especially for mechanical systems. Nonlinear Control Systems ME-523 Analysis of nonlinear systems is performed towards controlling them. Stability in the sense of Lyapunov is introduced, together with geometrical methods (Exact Feedback Linearization). Various examples are treated (pen and pencil, and computer).