Skip navigation
  • Home
  • Browse
    • Communities
      & Collections
    • Browse Items by:
    • Publication Date
    • Author
    • Title
    • Subject
    • Department
  • Sign on to:
    • My MacSphere
    • Receive email
      updates
    • Edit Profile


McMaster University Home Page
  1. MacSphere
  2. Departments and Schools
  3. Faculty of Engineering
  4. Department of Mechanical Engineering
  5. Mechanical Engineering Publications
Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31262
Title: Air-LUSI: Estimation, Filtering, and PID Tracking Simulation
Authors: Cataford A
Gadsden SA
Turpie K
Biglarbegian M
Department: Mechanical Engineering
Keywords: 4007 Control Engineering, Mechatronics and Robotics;40 Engineering;4001 Aerospace Engineering;4010 Engineering Practice and Education
Publication Date: 13-May-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Abstract: This paper describes the development of a two degree of freedom (2DoF) pointing and tracking simulation used for evaluating the Air-LUSI subsystem behaviour. The Air-LUSI project intends on obtaining high altitude Lunar Spectral Irradiance (LUSI) measurements of the Moon by integrating an automated telescope mount capable of acquiring the Moon as a target and tracking it from the science pod of an ER-2 aircraft as it flies at an altitude of 65, 000 feet. By obtaining precise measurements of the Lunar Spectral Irradiance, a Lunar Calibration Model can be used for NASA's Earth Observing System (EOS). The simulations found within this report describe the estimation, filtering, and control strategies applied to the 2DoF gimbal design and compares the tracking accuracy when using system measurements or state estimates produced by the linear Kalman filter (KF) or the nonlinear unscented Kalman filter (UKF) as the input to the PID controller. An additional aspect of this project studies the nonlinear or linear system behaviour described by the interacting multiple model (IMM) algorithm and analyzes the results of a hybrid adaptive control strategy that combines the KF and UKF PID gains using the IMM mode probabilities.
URI: http://hdl.handle.net/11375/31262
metadata.dc.identifier.doi: https://doi.org/10.1109/ccece.2018.8447850
ISSN: 0840-7789
Appears in Collections:Mechanical Engineering Publications

Files in This Item:
File Description SizeFormat 
074-gadsden_conf_074.pdf
Open Access
Published version269.92 kBAdobe PDFView/Open
Show full item record Statistics


Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.

Sherman Centre for Digital Scholarship     McMaster University Libraries
©2022 McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L8 | 905-525-9140 | Contact Us | Terms of Use & Privacy Policy | Feedback

Report Accessibility Issue