Princeton University

School of Engineering and Applied Science

Department of Mechanical and Aerospace Engineering

*Optimal Control and Estimation* is a graduate course that presents the theory and application of optimization, probabilistic modeling, and stochastic control to dynamic systems. Particular attention is given to modeling dynamic systems, measuring and controlling their behavior, and developing strategies for future courses of action.

Twenty-four 80-minute seminars are held during the term (see Syllabus). The slides used at the seminars are presented here. The portable document files may be downloaded for non-commercial, educational use only, with acknowledgment of the source. Several graphics found on the web are included without attribution. Any graphic material that is deemed to infringe on another's copyright will be promptly removed upon formal notification by the copyright holder.

- Seminar 1: Overview and Preliminaries
- Seminar 2: Minimization of Static Cost Functions
- Seminar 3: Principles for Optimal Control: Necessary & Sufficient Conditions, Euler-Lagrange Equations
- Seminar 4: Principles for Optimal Control: Minimum Principle, Dynamic Programming, Terminal Contraint
- Seminar 5: Path Constraints and Numerical Optimization
- Seminar 6: Minimum-Time and Minimum-Fuel Trajectory Optimization
- Seminar 7: Neighboring-Optimal Control
- Seminar 8: Stability of Dynamic Systems
- Seminar 9: Linear-Quadratic Regulators
- Seminar 10: Cost Functions and Controller Structures
- Seminar 11: Linear-Quadratic Control System Design
- Seminar 12: Modal Properties of Linear-Quadratic Systems
- Seminar 13: Spectral Properties of Linear-Quadratic Systems
- Seminar 14: Singular-Value Analysis of Linear-Quadratic Systems
- Seminar 15: Probability and Statistics
- Seminar 16: Least-Squares Estimation for Static Systems
- Seminar 17: Propagation of Uncertainty in Dynamic Systems
- Seminar 18: State Estimation (Kalman Filter) for Discrete-Time Systems
- Seminar 19: State Estimation (Kalman-Bucy Filter) for Continuous-Time Systems
- Seminar 20: Nonlinear State Estimation (Extended Kalman Filters)
- Seminar 21: Nonlinear State Estimation (Sigma-Points and Particle Filters)
- Seminar 22: Adaptive State Estimation
- Seminar 23: Stochastic Optimal Control
- Seminar 24: Linear-Quadratic-Gaussian (LQG) Controllers

Lecture Slides for Robotics and Intelligent Systems.

Lecture Slides for Space System Design.

Seminar Slides for From the Earth to the Moon.

**MAE 546, Optimal Control and Estimation**

Last updated May 24, 2017, stengel@princeton.edu.

Copyright 2017 by Robert F. Stengel. All rights reserved.