Networked and Distributed Control Systems (NDCS)

Lecturers

Objectives

  • to analyze the topological properties of networked systems by using graph theory
  • to study the behavior of networked systems in continuous and discrete time
  • to design coupling laws for networked systems
  • to solve optimization problems originating from Model Predictive Control or Machine Learning in a distributed way

Contents

  • Elements of matrix and graph theory

  • The Laplacian matrix

  • Averaging systems in continuous-time and discrete-time domains

  • Diffusively coupled linear systems

  • Control design for averaging and synchronization

  • Distributed optimization strategies

Literature

  • Lecture Material
  • F. Bullo. Lectures on Network Systems, 2019
  • J. Lunze. Networked Control of Multi-Agent Systems, 2019
  • M. Mesbahi and M. Egerstedt. Graph Theoretic

Recommend Prerequisites

  • Content of the courses Linear and Nonlinear Control Systems, and Optimization Methods

Credits

2L + 1T, 3 Credits
(L: lecture hours per week, T: tutorial hours per week)
The course is offered in the summer semester; the examination in the winter and summer semester (in English only).

Course Number

- to be inserted -

Assignment to Course Programs

Master of Electrical Engineering

Master of Mechatronics

Open as elective course within other Master programs

Additional Information, Course Content, and Teaching Material / Moodle