The first notebook introduces important concepts from Control Theory and tackles the problem of stabilizing a mass-spring-damper system and an inverted pendulum on a cart using Full-state Feedback and PID.
The second notebooks introduces Optimal Control, Dynamic Programming and shows the parallels between Optimal Control and Reinforcement Learning. It tackles the problem of stabilizing the same two systems using LQR and MPC with iLQR.
Changes
Created modified Inverted Pendulum gymnasium environment that allows changing the cutoff frequency.
Added control dependencies.
Added content to Introduction to Control notebook.
Added content to Control and Planning notebook.
Created Mass-Spring-Damper environment.
Disabled mypy pre-commit hook.
Adapted Dockerfile (use poetry and add missing dependencies).
Changes