Flight System Identification and Parameter Estimation

Key Facts
Contact Michael Bachfischer M.Sc.
Language of Instructions German or English (depending on the audience)
Language of Materials English
Type / ECTS Lecture / 5
Semester Summer Semester
Time and Place Tuesdays, 8.15-9.45 (TUM-Online)
Thursday, 10.00-10.45 (TUM-Online)
Related Links moodle.tum.de
Prerequisites No special prerequisites are necessary, however basics in the following topcs facilitate the learning process:

  • Signal processing
  • System’s theory
  • Control theory
  • Optimization
  • Flight mechanics, control and testing
Content / Educational Objectives Exact mathematical models become more and more important in the development of technical systems. One way to obtain them is to determine the model structure and its parameters based on experimental results. A well-established set of statistical methods exist to achieve this goal, which forms the basis of this lecture. Details on the application of these strategies and algorithms to the modeling and identification of dynamic systems are discussed during the course of the lecture.
Lecture examples focus on manned and unmanned aircraft. However, the theory can be applied to any (dynamic) system, thus a flight mechanics background is not absolutely necessary.The lecture consists of the following chapters:

  1. Introduction and Motivation
  2. Flight Vehicle Instrumentation
  3. Mathematical Modeling
  4. Estimation Theory
  5. Estimation of Static Models
  6. State Estimation
  7. Maximum Likelihood Methods
  8. Methods Specific for linear Dynamic Systems
  9. Online Identification
  10. Experiment Design
  11. Model Validation
Teaching Methods / Materials Lecture notes can be purchased from the ‘Fachschaft’.
Exam The exam is oral. Exact dates will be organized on an individual basis.
Reference Literature
  • Klein, V., & Morelli, E. A. (2006). Aircraft system identification: Theory and practice. Reston, VA: American Institute of Aeronautics and Astronautics.
  • Jategaonkar, Ravindra V. (2006). Flight Vehicle System Identification – A Time Domain Methodology – Progress in Astronautics and Aeronautics, Volume 216. American Institute of Aeronautics and Astronautics.

This lecture is part of the Munich Aerospace Teaching Collaboration.

SysID Lecture Overview