Explores the contrasting mindsets of AI and control theory, focusing on the limits and practical challenges of optimal control in sequential decision-making.
Explores the theoretical links between optimization algorithms (like gradient descent) and control theory, analyzing them as dynamical systems.
Lecture on control theory, exploring PID controllers and their role in taming complex systems, from steam engines to modern robotics.
Explores Lyapunov's two methods for stability analysis in dynamical systems, focusing on linearization vs. potential functions.
A control theory blog post reframing stability analysis as the study of homeostasis and life, not death, using biological regulation as motivation.
A lecture blog exploring surprising robustness and fragility in interconnected systems, drawing analogies between nonlinear control and optimization.
A lecture on control theory, explaining feedback as an algebraic interconnection for robust system design, using amplifier gain as an example.
A syllabus for a university course exploring the principles of feedback, control theory, and their connections to machine learning and optimization.
A professor reflects on the intersection of machine learning and control theory, discussing the Learning for Dynamics and Control (L4DC) conference and the need for a merged perspective.
