Note: This is an archived Handbook entry from 2009. Search for this in the current handbook
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2009:Semester 2, - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: Thirty-six hours of lectures, 12 hours of tutorials, laboratory or project work. |
Total Time Commitment: Not available
431-324 Control 1 (Classic Control) (prior to 2004 System Modelling and Control)
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorAssoc Prof Isaac Kao
On completion of this subject, students should have a good understanding of state-space discrete-time controller design methods and the MATLAB software package to perform such design.
Topics include: motivation for advanced MIMO control; Industrial examples. Revision: input/output and state space models of LTI continuous-time and discrete-time systems. Discretisation of the plant with a zero order hold. Similarity coordinate transformations. Relations of transfer function and state space representations. Controllability and stabilisability. Observability and detectability. Kalman canonical decomposition. Pole-zero cancellation and relation to controllability/observability. Pole assignment by state feedback. Ackerman's formula. Observers. Separation principle. Internal model principle. Tradeoffs in controller/observer design. Optimal controller design (LQR deterministic and LQR and LQG). Optimal observer design (LQR and LQG). Connections of optimal control and estimation to pole assignment. Achieving integral action in LQR synthesis. Predictive control. Design study: an industrial application.
Project: Modelling, analysis, controller design and implementation for a particular plant (on some of our lab equipment.)
On completing this subject the student will be able to:
1. Apply fundamental state-space techniques in the analysis and design of linear feedback control systems, as they arise in a variety of contexts;
2. Formulate control engineering problems in terms of optimising an objective function subject to constraints;
3. Use software tools to simulate and design the linear control systems.
Five homework assignments. Solutions of each assignment should be less than 10 A4 pages long using 12 pt font. (20%). One mid-semester test (20%). One 3-hour written final examination (60%).
|Recommended Texts:|| |
Information Not Available
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
Bachelor of Engineering (Biomedical)Biosignals |
Bachelor of Engineering (Computer Engineering)
Bachelor of Engineering (Electrical Engineering)
Bachelor of Engineering (Software Engineering)
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