Undergraduate - UnitMEC3457 - Systems and control

• Understand the significance and relevance of systems and associated control in engineering.
• Appreciation for mathematical formulations to develop accurate linear models through classical and state space modelling techniques describing systems with single-input single-output (SISO) and multi-input and multi-output (MIMO).
• Gain knowledge of system's response through the use of analytical techniques, such as classical solution, Laplace transforms, state space, etc.
• Understand the concept of stability and its importance for systems analysis and control.

Gain knowledge of dynamic performance of a system, including selection of system parameters to achieve the desired response, and further analysis through techniques such as frequency response.

• Understand the effects of non-linearity in systems and limitations of the use of linear models.
• Gain knowledge of experimental, as well as computer-based (such as Matlab) techniques.
• Ability to develop mathematical models for devices and systems for the purpose of response and dynamic behaviour analysis.
• Ability to obtain system's solution and response using classical method, Laplace transforms method, and state space method.
• Ability to determine the stability of a system utilising S-plane and Routh-Hurwitz technique.
• Ability to analyse dynamic performance of systems in the time and frequency domains using the Bode plot, root-locus, and Nyquist plot.
• Ability to continue learning about systems modelling and control techniques beyond the content provided in this course.
• An appreciation of the unified concept of resistance, capacitance and inertia/indusctance to perform physical modelling of mechanical, fluidic, hydraulic and pneumatic systems.
• An appreciation for the need to represent, predict and analyse the system and its response and dynamic performance, and convey these through pictorial representations such as block diagrams, signal flow graphs, plots, etc
• An appreciation of non-linear effects and the use of linear models as approximation.