STATE SPACE SYSTEMS ANALYSIS

Prerequisites & course information

Requisites: E C E 330 , MATH 319 , 320 , 376 , or member of Engineering Guest Students Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Formulate state-space models of engineering systems Audience: Undergraduate 2. Understand solutions of ordinary differential equations (ODE) and visualize them using vector fields and phase portraits Audience: Undergraduate 3. Linearize nonlinear state-space models and understand the limitations of linear systems analysis Audience: Undergraduate 4. Solve a system of linear differential equations using matrix exponentials, diagonalizations, and Jordan normal forms Audience: Undergraduate 5. Systematically analyze linear state-space systems using matrix methods Audience: Undergraduate 6. Understand and fluently use concepts such as: time-invariance, stability, controllability, and observability Audience: Undergraduate 7. Design linear state-feedback controllers and observers Audience: Undergraduate Learning Outcomes: 1. Formulate state-space models of engineering systems Audience: Undergraduate 2. Understand solutions of ordinary differential equations (ODE) and visualize them using vector fields and phase portraits Audience: Undergraduate 3. Linearize nonlinear state-space models and understand the limitations of linear systems analysis Audience: Undergraduate 4. Solve a system of linear differential equations using matrix exponentials, diagonalizations, and Jordan normal forms Audience: Undergraduate 5. Systematically analyze linear state-space systems using matrix methods Audience: Undergraduate 6. Understand and fluently use concepts such as: time-invariance, stability, controllability, and observability Audience: Undergraduate 7. Design linear state-feedback controllers and observers Audience: Undergraduate