Notes
Working notes on control and multi-agent systems. They are organised as an overview rather than a course: enough to place a problem, with pointers to what to read next.
Control theory
Describing a robotic system, and designing the law that drives it.
What a model is made of and the handful of distinctions that decide which controllers are available to you: linear or nonlinear, continuous or discrete time, fully actuated or underactuated, nominal or uncertain.
The small library of models that covers most of robotics, written in a common form with their dimensions and structure.
Brief overview of the key techniques for designing control laws, through to designing under disturbance, unknown parameters, and hard safety constraints.
Things about CBF-QP I keep getting confused on.
Defining safety in the context of control.
A safety filter that runs two controllers (performance and safety driven) and searches for the latest switching time the system can still be safe while remaining on the performance-driven controller.
Resilient network theory
What the communication graph has to look like when some agents cannot be trusted.
Optimization and Learning
Understanding the theories of optimization and machine learning tools.
Corrections and suggestions are welcome by email.