control-systems
4 free lessons tagged control-systems across Robotics. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Trajectory Generation and Tracking
Learn how to generate smooth robot trajectories — trapezoidal velocity profiles, cubic and quintic polynomials — and how to combine feedforward and feedback to track them with minimal error on real arms and mobile robots.
State-Space Models and Pole Placement
Move beyond single-input PID to the state-space framework: the state vector, matrix dynamics, controllability, pole placement via state feedback, and LQR — the tool that scales to full robot arms and drones.
PID Controllers
Master the proportional-integral-derivative controller: what each term fixes, the PID equation, integral windup, a discrete Python implementation, and a Ziegler-Nichols tuning guide for real loops.
Feedback Control Fundamentals
Understand why feedback beats open-loop, how the classic closed-loop architecture works, and what the key performance metrics — rise time, overshoot, settling time, steady-state error — actually mean for a real system.