units

MAE3408

Faculty of Engineering

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Monash University

Monash University Handbook 2011 Undergraduate - Unit

6 points, SCA Band 2, 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

LevelUndergraduate
FacultyFaculty of Engineering
OfferedClayton Second semester 2011 (Day)
Coordinator(s)C 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 and optimal control via kalman filtering. Linear quadratic optimal controllers. The equations of motion for dynamic systems with controllers determined with computational analysis in Matlab.

Objectives

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)

Professor Mark Thompson

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

MAE3404