units

MAE3408

Faculty of Engineering

Undergraduate - Unit

This unit entry is for students who completed this unit in 2013 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

print version

6 points, SCA Band 2, 0.125 EFTSL

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LevelUndergraduate
FacultyFaculty of Engineering
Organisational UnitDepartment of Mechanical and Aerospace Engineering
OfferedClayton Second semester 2013 (Day)
Coordinator(s)Dr Chao Chen

Synopsis

This unit covers control theory for aerospace systems with the use of state-space techniques. The state-space of dynamic systems and resulting equations are covered. Concepts of controllability, observability, detectability and the state-transition matrix follow. Classical control concepts including root-locus and frequency-response techniques are set in context of their importance in robust control. Compensators for aerospace systems with full and reduced-order linear observers, parametric optimization. Linear quadratic optimal controllers. The equations of motion for dynamic systems with controllers determined with computational analysis in Matlab.

Outcomes

  • An understanding of the role of linear algebra in engineering dynamics and controls.
  • An understanding of modern control theory and its use in aerospace systems.
  • The concepts of controllability, stabilizability, observability, and detectability and their use in controllers.
  • An appreciation for optimization techniques, particularly those applied to optimum controllers.
  • The knowledge of where to go to learn more beyond the content of the course on related and more advanced topics.
  • A well-rounded individual ability to conduct control system analysis and design via independent hand and computer calculations in Matlab.
  • An individual ability to determine the behaviour of simple aerospace dynamic systems and develop strategies to control that behavior, qualitatively and quantitatively.
  • An individual ability to determine the state-transfer matrix, determine the SISO transfer function, design regulators and full/reduced-order/linear quadratic control observers.
  • An individual ability to optimize a dynamic system based on the mathematical model of the system and linear optimization theory.
  • Presenting student work in a cogent and concise manner.

Assessment

Examination (3 hours): 70%
Practice classes 20%
Computer laboratory exercise: 10%

Chief examiner(s)

Contact hours

Six hours of contact time per week - usually 3 hours lectures and 3 hours practice sessions or laboratories as well as 6 hours of private study per week

Prerequisites