Courses
Here is a list of my courses given during the last five years:
For more informations, please the dedicated page in Chamilo.
Optimization: This course covers the principal algorithms for linear, nonlinear, dynamic optimization and optimal control. Topics include the simplex method, optimality conditions for non-linear optimization, Newton’s method, heuristic methods, and dynamic programming and optimal control methods.
Modeling and control under state representation: This course includes state-space methods of feedback control system design and design optimization for invariant continuous systems; pole positioning, observability, controllability, observer design, the linear quadratic optimal regulator problem, Lyapunov functions and stability theorems. Examples are be drawn from mechanical, electrical and hydraulic engineering applications. MATLAB is used extensively during the course for the analysis, design and simulation.
Old courses
Predictive and nonlinear control: Numerical application of Predictive and nonlinear control on real industrial applications.
Optimization for energy systems: This course is devoted to industrial applications of optimization in the electricity production, transport and distribution. The tools for continuous optimization (linear programming and nonlinear) are applied to the problem of optimal power flow, while the unit commitment problem is submitted to the tools of combinatorial optimization (linear integer programming).
Linear systems: The course addresses dynamic systems, i.e., systems that evolve with time and how the input affects the output. In particular, we concentrate on systems that can be modeled by Ordinary Differential Equations (ODEs) or transfer functions, and that satisfy certain linearity and time-invariance conditions. The response of these systems to inputs and initial conditions is analyzed and in particular interest systems obtained as interconnections of two or more other systems. Design of control systems that ensure desirable properties (like stability and performance) is also addressed.
Embedded control: This course aims to introduce the model development methodology of embedded control systems. The course contains a reminder of the basic knowledge of automatic control, design tools, embedded programming languages. As a research project, using a Lego Mindstorms NXT robot, students learn and practice all the steps of model development chain modeling, controller design, validation, simulation, and implementation of the controller in the Mindstorms robot.
Innovation and management: In this course students work in a project mode on the generation of an innovative concept and its development, both technically and in its ability to generate value. They implement creativity techniques starting from a given issue to bring out an innovative concept that will be the object of study. They identify and formalize the innovative concept technically and learn the main market segmentation techniques to apply the concept to identify target markets. They formalize the broad outlines of a business model: possible scenarios, revenue models, risks and profit opportunities.
Control of power networks: Computer sessions using PSAT toolbox.
Robots control: Application on Lego mindstroms NXT, Thymio, arduino.
Collectif engineering projects: Second year ENSE3 students.
Integration projects: For third year ASI students.
Matlab and Simulink.
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