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AERO4701: Space Engineering 3 (2015 - Semester 1)

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Unit: AERO4701: Space Engineering 3 (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Senior Advanced
Faculty/School: School of Aerospace, Mechanical & Mechatronic Engineering
Unit Coordinator/s: Prof Sukkarieh, Salah
Session options: Semester 1
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: AERO3760.
Brief Handbook Description: This UoS aims to teach students the fundamental principles and methods of designing solutions to optimal estimation and control problems in space engineering applications. Students will apply learned techniques in optimal estimation and control theory to solving a wide range of different problems in engineering such as satellite orbit determination, satellite attitude determination, satellite positioning systems and remote sensing, optimal flight control, space shuttle re-entry and orbit transfers. Students will learn to recognize and appreciate the coupling between the different elements within an estimation and control task, from a systems-theoretic perspective.
Assumed Knowledge: None.
Lecturer/s: Gan, Jason
Prof Sukkarieh, Salah
Tutor/s: Miss Kaushalya Madugalle - k.madugalle@acfr.usyd.edu.au
Timetable: AERO4701 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Tutorial 2.00 1 13
3 Independent Study 4.00 1 13

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
Students will work on implementing solutions to estimation and control tasks involving the design of different algorithms and systems. Design (Level 4)
Students will apply optimal estimation and control design theory to a number of key problems in aerospace engineering such as satellite attitude and orbit determination systems, satellite remote sensing and mapping, optimal flight control, reentry and orbit transfer Engineering/IT Specialisation (Level 5)
Students will develop an expertise in the fundamental principles and applications of optimal estimation and control methods including the use of linear and non-linear least squares approximations, and non-linear programming for various engineering tasks. Maths/Science Methods and Tools (Level 4)
Students will be required to conduct their own literature search in studying past solutions to example problems and draw upon this knowledge during their own design process. Information Seeking (Level 4)

For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Engineering/IT Specialisation (Level 5)
1. The ability to recognize and appreciate the coupling between the different elements within an estimation and control task, such as satellite remote sensing and orbit transfer, from a systems-theoretic perspective.
Maths/Science Methods and Tools (Level 4)
2. The ability to apply learned techniques in optimal estimation and control theory to solving a wide range of different problems in engineering.
Design (Level 4)
3. The ability to use this system knowledge and basic design principles to design and test a solution to a given estimation and conrol task, with a focus on space applications (such as satellite remote sensing, orbit transfers and reentry).
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Assignment 1 No 30.00 Week 4 1, 2,
2 Assignment 2 No 30.00 Week 8 1, 2, 3,
3 Assignment 3 No 40.00 Week 13 1, 2, 3,
Assessment Description: Assignment: Assignment 1 will focus on satellite mission design, the simulation of satellite orbits and the determination of satellite orbit parameters from range and line-of-sight observations.

Assignment: Assignment 2 will focus on the application of least squares estimation with relation to the operation of GNSS.

Assignment: Assignment 3 will focus on optimal control techniques and its application to space systems. The assignment will also look into the integration of estimation and control techniques.
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: See the policies page of the faculty website at http://sydney.edu.au/engineering/student-policies/ for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Introduction to estimation in aerospace applications: Remote sensing and navigation systems, overview of sensors and systems.
Week 2 Orbital Mechanics and Space Geometry: Aerospace frames of reference, Keplerian orbital mechanics, orbital perturbations. Orbital Mechanics and Orbit Determination: Satellite coverage and multi-satellite constellations, orbit determination through range and line-of-sight measurements.
Week 3 Introduction to Estimation and Least Squares: Linear least squares, constrained and weighted least squares, non-linear least squares.

GNSS I: Introduction to GPS, signals and message structure, orbit geometry, orbit calculation using almanac and ephemeris data, ground tracking of GPS satellites, operation of positioning, error sources.
Week 4 GNSS II: Orbit determination using non-linear least squares, GPS accuracy quantification, dilution of precision, introduction to probability and statistics of errors.
Assessment Due: Assignment 1
Week 5 Attitude Determination Systems (ADS) I: Magnetic sensing, sun/star tracking, horizon scanners, sensor modeling and error simulation.

Attitude Determination Systems (ADS) II: Focus on attitude representation, ADS methods, least squares for ADS.
Week 6 Introduction to optimal control in aerospace applications. Optimal control theory, analytical approach and numerical approach.
Week 7 Numerical optimisation strategies. Formulation of Equality Constrained Problem and solution approach.
Week 8 Formulation of Inequality Constrained Problem and solution approach.
Assessment Due: Assignment 2
Week 9 Formulation of optimal control problem as a nonlinear program
Week 10 Advance optimal control strategies: Transcription Method
Week 11 Combining estimation and control
Week 12 Applied Optimal Control: Example

Support for final assignment.
Week 13 Applied Optimal Control: Example

Support for final assignment.
Assessment Due: Assignment 3

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Aeronautical Engineering (Space) / Commerce 2010, 2011, 2012, 2013, 2014
Aeronautical (Space) 2010, 2011, 2012, 2013, 2014, 2015
Aeronautical Engineering (Space) / Arts 2011, 2012, 2013, 2014
Aeronautical Engineering (Space) / Medical Science 2011, 2012, 2013, 2014
Aeronautical Engineering (Space) / Project Management 2012, 2013, 2014
Aeronautical Engineering (Space) / Science 2011, 2012, 2013, 2014
Aeronautical Engineering (Space) / Law 2010, 2011, 2012, 2013, 2014
Aeronautical (Space) / Arts 2015
Aeronautical (Space) / Commerce 2015
Aeronautical (Space) / Medical Science 2015
Aeronautical (Space) / Project Management 2015
Aeronautical (Space) / Science 2015
Aeronautical (Space) / Law 2015
Mechanical (Space) 2015, 2010, 2011, 2012, 2013, 2014
Mechanical (Space) / Arts 2015
Mechanical (Space) / Commerce 2015
Mechanical (Space) / Medical Science 2015
Mechanical (Space) / Project Management 2015
Mechanical (Space) / Science 2015
Mechanical (Space) / Law 2015
Mechatronic (Space) 2015, 2010, 2011, 2012, 2013, 2014
Mechatronic (Space) / Arts 2015
Mechatronic (Space) / Commerce 2015
Mechatronic (Space) / Medical Science 2015
Mechatronic (Space) / Project Management 2015
Mechatronic (Space) / Science 2015
Mechatronic (Space) / Law 2015
Mechanical Engineering (Space) / Arts 2011, 2012, 2013, 2014
Mechanical Engineering (Space) / Commerce 2010, 2011, 2012, 2013, 2014
Mechanical Engineering (Space) / Medical Science 2012, 2013, 2014
Mechanical Engineering (Space) / Project Management 2012, 2013, 2014
Mechanical Engineering (Space) / Science 2011, 2012, 2013, 2014
Mechatronic Engineering (Space) / Arts 2011, 2012, 2013, 2014
Mechatronic Engineering (Space) / Commerce 2010, 2011, 2012, 2013, 2014
Mechatronic Engineering (Space) / Medical Science 2012, 2013, 2014
Mechatronic Engineering (Space) / Project Management 2012, 2013, 2014
Mechatronic Engineering (Space) / Science 2011, 2012, 2013, 2014
Mechatronic Engineering (Space) / Law 2010, 2011, 2012, 2013, 2014

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
Engineering/IT Specialisation (Level 5) Yes 38.33%
Maths/Science Methods and Tools (Level 4) Yes 38.33%
Design (Level 4) Yes 23.33%
Information Seeking (Level 4) Yes 0%

These goals are selected from Engineering & IT Graduate Outcomes Table which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.