Applied Trajectory Optimization Certificate- Curriculum 299
Program Manager
Mark Karpenko
WA-306
(831) 656-3231
mkarpenk@nps.edu
Academic Associate
Isaac M. Ross
WA-323
(831) 656-2074
imross@nps.edu
Brief Overview
This certificate program provides students a suite of practical mathematical tools for applying trajectory optimization techniques to solve various problems in engineering design and optimization. The coursework equips students with an ability to model various dynamical systems and formulate a collection of dynamic optimization problems that explore the engineering trade-space. Two of the four-course sequence may be chosen as track electives to meet a student's particular interest in an engineering system. A capstone course provides the mathematical and computational framework that are necessary to apply the tools to address a trajectory optimization problem related to a practical system chosen by the student.
A minimum of 15 credit hours must be completed.
Requirements for Entry
For entry, the student must have a baccalaureate degree with:
1. An APC score of 222
2. Acceptance by the MAE Department
Program Length
Four quarters.
Graduate Certificate Requirements
To earn the academic certificate students must pass all four courses with a C+ (2.3 Quality Point Rating (QPR)) or better in each course and an overall QPR of 3.0 or better. Students earning grades below these standards will need to retake the courses to bring their grades within standards or they will be withdrawn from the program.
Outcomes
This certificate program provides students a suite of practical mathematical tools for applying trajectory optimization techniques to solve various problems in engineering design and optimization. The coursework equips students with an ability to model various dynamical systems and formulate a collection of dynamic optimization problems that explore the engineering trade-space.
Explain the major deficiencies and challenges in current guidance systems in a mathematically justifiable manner.
Understand the scientific underpinnings of trajectory planning and guidance.
Achieve proficiency at the engineering level of the mathematics of constraint satisfaction, their violations and their impacts on practical flight.
Understand first-hand the emerging tools and techniques for verification and validation of prototypical flight codes.
Achieve proficiency in implementation of trajectory planning and guidance algorithms.
Demonstrate a flyable end-to-end algorithm for a platform of their choice.
Required Courses
Quarter 1
Track Electives (choose one)
| AE3818 | Spacecraft Attitude Dynamics and Control | | 3 | 2 |
| AE4816 | Dynamics and Control of Space Structures | | 4 | 0 |
| AE4818 | Acquisition, Tracking, and Pointing of Military Spacecraft | | 3 | 2 |
| AE4820 | Robotic Multibody Systems | | 3 | 2 |
| EC4310 | Fundamentals of Robotics | | 3 | 2 |
| AE4362 | Astrodynamics | | 3 | 0 |
| ME3801 | Dynamics and Control of Marine and Autonomous Vehicles I | | 3 | 2 |
| ME4703 | Missile Flight and Control | | 4 | 1 |
| ME4822 | Guidance, Navigation, and Control of Marine Systems | | 3 | 2 |
| MX3001 | Basic Engineering Concepts in Modeling and Simulation I | | 4 | 0 |
| PH3152 | Analytical Mechanics | | 4 | 0 |
| PH4153 | Advanced Classical Mechanics I | | 4 | 1 |
| AE3820 | Advanced Mechanics and Orbital Robotics | | 3 | 2 |
| AE3815 | Spacecraft Rotational Mechanics | | 3 | 2 |
Quarter 2
Track Electives (choose one)
| AE3830 | Aerospace Guidance and Control | | 3 | 2 |
| MA4311 | Calculus of Variations | | 4 | 0 |
| ME4800/AE4800 | Machine Learning for Autonomous Operations | | 3 | 2 |
Quarter 3
Quarter 4
| ME4881 | Aerospace Trajectory Planning and Guidance | | 2 | 4 |