System states and state space models. Linearization of nonlinear state-space models. Solving linear time-invariant state-space equations. Controllability and observability, and their algebraic tests. Minimal state-space realizations. State feedback and eigenvalue/pole assignment. Step tracking control design. State estimation and observer design. Observer-based control. Introduction to linear quadratic optimal control. Prerequisite: MCTR 320.