3 credits
Spring 2026 Lecture Distance Learning Upper Division
This course introduces students to analysis and synthesis methods of optimal controllers and estimators for (stochastic) dynamical systems. The topics in this course include a review of probability and stochastic processes, classical estimation techniques, Pontryagin's maximum principle, dynamic programming. Linear Quadratic Regulator problems (LQR), Kalman filter, duality of LQR with Kalman filter, Linear Quadratic Gaussian (LQG), and a range of engineering applications.
Learning Outcomes1Study analysis and synthesis methods of optimal controllers and estimators for stochastic dynamical systems.
2Present a review of probability and random processes, calculus of variations, dynamic programming, Maximum Principles, optimal control and estimation, duality, and optimal stochastic control.
3Learn how to effectively communicate their ideas and how to formulate a problem and solve it.
Prerequisites
Restrictions
made by Purdue students.