Optimal Control Techniques for Unpiloted Aerial Vehicles (UAVs)
- This unique guided online course covers the application of optimal control theory for unmanned aerial vehicles (UAVs).
- All students will receive an AIAA Certificate of Completion at the end of the course
OVERVIEW
This unique guided online course (approx. 10-hours of self-study, with weekly classes/discussions) covers the application of optimal control theory for unpiloted aerial vehicles (UAVs). The theoretical topics introduced are: variational necessary conditions for optimal control and the Pontryagin Minimum Principle; the Legendre pseudospectral method for direct numerical trajectory optimization; the linear quadratic regulator; and optimal path search methods on graphs. The discussion on these theoretical topics is focused on applications, and many intricate proofs are omitted. UAV application examples are demonstrated, including: autopilot design, reference trajectory tracking, optimal reference trajectory generation in drift (wind) fields and threat fields. Examples of recent advances in the state-of-the-art are discussed, and optional self-assessment problems are also included.
- Apply variational optimal control theory to find trajectories for aircraft models.
- Design LQR control laws for autopilot and trajectory tracking applications.
- Review and apply path optimization algorithms for planning in discretized environment models.
- Review and apply pseudospectral trajectory optimization techniques for numerical trajectory optimization.
AUDIENCE:
- Industry, Government, and Academia practitioners with interests in UAV trajectory design, optimization, and/or tracking applications.
- Graduate students: aerospace, robotics, or mechanical engineering majors with interests in practical UAV applications.
- Recommended Background is basic familiarity with ordinary differential equations, linear algebra, and introductory control theory, as covered in typical curricula for an undergraduate degree in Aerospace, Mechanical, or Electrical Engineering (e.g., familiarity with linear control theory and PID feedback control). Familiarity with aircraft dynamics is beneficial but not essential. The course material includes optional sample code in MATLAB®. To peruse this code, fluency with MATLAB® is required. To complete the optional self-assessment problems, which may be done independently of the sample code provided, fluency with at least one programming language suitable for scientific computations is required. Background Competency Self-Assessment
COURSE FEES (Sign-In to Register):
– AIAA Member: $595 USD
– Non-Member: $795 USD
– AIAA Student Member: $395 USD
This course is available on-demand. Register here.
OUTLINE:
The course material includes the following items:
- Video lectures: typically 20-30 minute videos that either cover a theoretical concept or demonstrate the application of theory to a problem. These videos are organized in sections (see list below) that may be viewed independent of each other (i.e., non-sequentially).
- Lecture notes: handouts of the slides used for videos, which provide a bare minimum of written technical material. Additional recommended reading references are also provided within the slides.
- Multiple self-assessment problems: most assignment problems require some computational work, for which functional MATLAB® code is provided as a reference to validate your work.
- Sample MATLAB® code for solving assigned problems.
The video lectures are organized as follows. Lecture durations are indicated in the parentheses:
- All course slides and additional references will be available for immediate download. No part of these materials may be reproduced, distributed, or transmitted, unless for course participants. All rights reserved.
- Weekly discussion groups will be delivered via a Zoom virtual classroom. Connection information will be provided to registrants near to the course start date. Test your connection here: https://zoom.us/test
Guided Self-Study Schedule
Watch video lectures and attempt self-assessment problems during the week per the suggested schedule below. Prepare questions to ask during the mid-week (Wednesday) live sessions. These sessions are intended to be student-driven office hour-type sessions where the self-assessment problems will be discussed.
| Lectures to watch | Self-assessment problems to attempt | Mid-week live session topics | |
| Week 1 | 1a) – 1f); 2a) – 2c) | 1, 2 | May 28 Introductory Ideas |
| Week 2 | 2a) – 2c), 3a) – 3c) | 3, 4, 5 | June 4 Direct Numerical Trajectory Optimization |
| Week 3 | 3d) – 3f), 4a) | 6, 7 | June 11 Variational Optimal Control |
| Week 4 | 4b), 4c), 5a), 5b) | 8, 9, 10 | June 18 LQR, Optimal Paths in Graphs |
Email: [email protected]
AIAA Training Links
-
For information, group discounts,
and private course pricing, contact:
Lisa Le, Education Specialist ([email protected])