About

This course will introduce you to modern control paradigms through the use of theoretical foundations and an emphasis on numerical methods and optimization. Proofs and in-depth theoretical reasoning, on the other hand, will be avoided whenever possible (due to time constraints and the amount of material).

The concepts covered in this class are based on technologies that, in my opinion, are not only fascinating from a theoretical standpoint but also have important applications in the real world. That said, the reviewed algorithms are by no means a magic bullet for fixing all of your control issues. However, it might shed light on the state of the art in the modern control theory.

Structure of the course

The course is consist of following parts:

• In Introduction and Modeling section, we will review the idea of a dynamical system and talk about some of the challenges that are associated with the practical implementation of controllers.

• Review of System Analysis and Control: review of system analysis, Lyapunov theory, stability, as well as linear and nonlinear control, with a primary emphasis on numerical tools.

• Optimization in Planning and Control: an overview of the optimization-driven methods, including MPC and Lyapunov-inspired methods, that are dedicated to the planning and control of linear and nonlinear systems.

• Identification and Data Driven Methods: In this chapter, we will investigate the algorithms that enable us to determine the parameters of abstract models based on the measurements taken from real plants, as well as construct models from scratch using these parameters.

• Other topics:: In this section, we will go over the ideas and some of the other interesting techniques, such as numerical analysis, including differential flatness, state observers, and sum-of-squares programming, amongst others. <!–
• Term project presentation (final exam): In the end you will apply one of the studied concepts and prepare the short (10-20 min) presentation.

Course organization

• We will have mixed lecture/practice format
• Almost each lecture is based on research paper which I will share with you.
• I highly encourage you to do hand written notes and not miss classes
• In the end each of you will have presentation (term project or paper/concept review) –>

Prerequisites

The following requirements must be met in order to effectively review course material and pass the final exam:

• It should NOT be your first course in control
• You should have basic background in differential equations, linear algebra and linear and nonlinear control, including stability analysis and Lyapunov theory.
• Familiar with convex optimization, linear, quadratic programming, linear matrix inequalities