Improved qualification and algorithms for illinisat-2 attitude determination and control

Vedant

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Description

Title

Improved qualification and algorithms for illinisat-2 attitude determination and control

Author(s)

Vedant

Issue Date

2018-04-27

Director of Research (if dissertation) or Advisor (if thesis)

• Coverstone, Victoria
• Ghosh, Alexander

Department of Study

Aerospace Engineering

Discipline

Aerospace Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

Attitude Determination and Control, Control Systems, Dynamic Programming, Trajectory Planning, Underactuated Control

Abstract

The University of Illinois has developed the IlliniSat-2 CubeSat bus, a generic scalable and modular design, utilizing commercially available off the shelf (COTS) parts. The Attitude Determination and Control System (ADCS) of the bus is purely magnetic, relying on magnetometers for determination and magnetorquers for actuation. The pure magnetic ADCS is favorable because of its low power, volume and mass contributions to the satellite’ platform, but this comes at the cost of weak system controllability and observability, and no flight heritage. To improve system reliability for operation in space, CubeSim, a hardware in the loop (HIL) simulation suite has been developed. The basic CubeSim setup consists of a tri-axial square Helmholtz cage (HC3), a dynamic power supply (PS), and a software package simulating the satellite’s attitude dynamics. This thesis is split into three parts, the first section discusses the different methods for calibrating the PS and the HC3 to generate desired magnetic fields, and HIL simulation results for traditional determination and control algorithms, using lab grade sensors. Next, using the calibrated basic CubeSim setup, calibration of flight sensors and HIL results are shown. The second part of the thesis discusses the hardware and software augmentation to the basic CubeSim for higher fidelity ADCS simulations, and the calibration of inertial sensors, necessary for increasing the observability of the ADCS. Finally, the third section discusses the trajectory generation for the underactuated pure magnetic ADCS, named as the “Navigation controller”, used to generate reference trajectories for the ADCS that is finite horizon optimal. The trajectory is obtained using two independent techniques, and the computational complexity and speed is compared for onboard usage.

Graduation Semester

2018-05

Type of Resource

text

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http://hdl.handle.net/2142/101238

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