Note: This unit is an archived version! See Overview tab for delivered versions.
AMME4500: Guidance, Navigation and Control (2013 - Semester 1)
| Unit: | AMME4500: Guidance, Navigation and Control (6 CP) |
| Mode: | Normal-Day |
| On Offer: | Yes |
| Level: | Senior Advanced |
| Faculty/School: | School of Aerospace, Mechanical & Mechatronic Engineering |
| Unit Coordinator/s: |
A/Prof Manchester, Ian
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| Session options: | Semester 1 |
| Versions for this Unit: |
| Campus: | Camperdown/Darlington |
| Pre-Requisites: | AMME3500. |
| Brief Handbook Description: | This unit introduces engineering design via optimization, i.e. finding the "best possible" solution to a particular problem. For example, an autonomous vehicle must find the fastest route between two locations over a road network; a biomedical sensing device must compute the most accurate estimate of important physiological parameters from noise-corrupted measurements; a feedback control system must stabilize and control a multivariable dynamical system (such as an aircraft) in an optimal fashion. The student will learn how to formulate a design in terms of a "cost function", when it is possible to find the "best" design via minimization of this "cost", and how to do so. The course will introduce widely-used optimization frameworks including linear and quadratic programming (LP and QP), dynamic programming (DP), path planning with A*, state estimation via Kalman filters, and control via the linear quadratic regulator (LQR) and Model Predictive Control (MPC). There will be constant emphasis on connections to real-world engineering problems in control, robotics, aerospace, biomedical engineering, and manufacturing. |
| Assumed Knowledge: | Students have an interest and a strong understanding of feedback control systems, specifically in the area of system modelling and control design in the frequency domain. |
| Lecturer/s: |
A/Prof Manchester, Ian
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| Timetable: | AMME4500 Timetable | |||||||||||||||||||||||||
| Time Commitment: |
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| T&L Activities: | Tutorial: Tutorials are constructed to provide a deeper understanding of the theoretical material. This will take the form of algorithm implementation in Matlab. Independent Study: Students will undertake independent study focussed primarily on completion of assignment work, refelction of theoretical material, and preperation for the quiz. Research: Students will be researching up on various reference articles provided and providing feedback on the material read in the form of a paper review. |
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 be given GNC tasks that will develop their skills in algorithmic implementation to meet the requirements of the problem. | Design (Level 4) |
| Students will be developing a deep level of understanding of the theoretical basis of GNC algorithms as well as practical skills in their implementation. | Engineering/IT Specialisation (Level 5) |
| Students will be reading the latest reference articles on GNC as applied to autonomous vehicles, and conducting their own literature search. | 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.
Design (Level 4)| Assessment Methods: |
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| Assessment Description: |
Assignment 1: Development of a simple path planning system for an autonomous vehicle. Assignment 2: Case study in optimal control design for a complex dynamical system. |
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| Grading: |
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| Policies & Procedures: | All university policies can be found at http://sydney.edu.au/policy Policies and request forms for the Faculty of Engineering and IT can be found on the forms and policies page of the faculty website at http://sydney.edu.au/engineering/forms |
| Recommended Reference/s: |
Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.
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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 control and guidance via optimization, and outline of course |
| Week 2 | Path planning over a road network (Dynamic Programming and A*) |
| Week 3 | Path planning over a road network (Dynamic Programming and A*) |
| Case Studies | |
| Week 4 | Optimisation |
| Week 5 | Optimisation |
| Case Studies | |
| Assessment Due: Assignment | |
| Week 6 | Control of Multivariable Systems |
| Case Studies | |
| Week 7 | Optimal Control |
| Week 8 | Optimal Control |
| Case Studies | |
| Assessment Due: Mid-semester quiz | |
| Week 9 | State Estimators |
| Week 10 | Kalman Filters |
| Week 11 | Real-Time Optimisation and Model Predictive Control |
| Week 12 | Advanced Case Studies |
| Assessment Due: Assignment | |
| Week 13 | Case Studies and Review |
| Exam Period | Assessment Due: Final exam |
Course Relations
The following is a list of courses which have added this Unit to their structure.
Course Goals
This unit contributes to the achievement of the following course goals:
| Attribute | Practiced | Assessed |
| Design (Level 4) | Yes | 30% |
| Engineering/IT Specialisation (Level 5) | Yes | 60% |
| Information Seeking (Level 4) | Yes | 10% |
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.
