Editorial path·Engineering·graduate·3 institutions

Linear Dynamics, Optimal Control & Underactuated Robotics

Matrix exponentials, stability eigenvalues, feedback regulators, and nonlinear locomotion

Progresses from Stanford EE263 linear dynamical systems and UW state-space control into MIT 6.832 nonlinear phase-portrait control for agile robots.

Start Step 16 steps · 6h total

Curriculum sequence

Step 1·Stanford University·Stephen Boyd·EE263· 1:16:46

Frames continuous and discrete linear dynamical models across circuits, mechanics, and estimation.

Step 2·Stanford University·Stephen Boyd·EE263· 1:05:52

Links linear input-output operators to impulse responses and state propagation.

Step 3·University of Washington·Steve Brunton·ME 564· 24:47

Derives canonical state-space ODEs and linearization around operating equilibria.

Step 4·University of Washington·Steve Brunton·ME 564· 19:30

Characterizes asymptotic stability through complex-plane eigenvalue geometry.

Step 5·MIT·Russ Tedrake·6.832· 1:25:07

Introduces underactuated mechanical systems where actuators are fewer than degrees of freedom.

Step 6·MIT·Russ Tedrake·6.832· 1:12:48

Uses nonlinear phase portraits and energy shaping to swing up and stabilize pendula.