MAE 6760

Last Updated

  • Schedule of Classes - April 13, 2023 2:00PM EDT
  • Course Catalog - April 12, 2023 7:14PM EDT

MAE 6760
Model-Based Estimation

Course information provided by the Courses of Study 2022-2023.

Course covers a variety of ways in which models and experimental data can be used to estimate model quantities that are not directly measured. Covers methods for solving the class of inverse problems that take the following form: given partial information about a system, what is the behavior of the whole system? Main estimation methods presented are batch least-squares-type estimation for general problems and Kalman filtering for dynamic system problems. Course deals with the issue of observability, which amounts to a consideration of whether a given inverse problem has a unique solution, and briefly covers the concept of statistical hypothesis testing. Techniques for linear and nonlinear models are taught. Both theory and application are presented.

When Offered Fall.

Prerequisites/Corequisites Prerequisite: linear algebra, differential equations, undergraduate-level probability theory, MATLAB programming. Prerequisite or corequisite: MAE 4780/MAE 5780 or ECE 5210.

View Enrollment Information

Syllabi:

  •   Regular Academic Session. 

  • 4 Credits Graded

  • 10128 MAE 6760   LEC 001

  •  
    • MW Upson Hall 222
    • Aug 22 - Dec 5, 2022

    • Campbell, M

  • Instruction Mode: In Person

Syllabi: none

  •   Regular Academic Session. 

  • 4 Credits Graded

  • 19982 MAE 6760   LEC 002

  •  

  • Instruction Mode: Distance Learning-Asynchronous
    Asynchronous online lecture only available to Mechanical Engineering and Systems Engineering distance learning off campus students. All other students will be unenrolled. All non-DL [distance learning] students should enroll in Lecture 1.