Introduction to control system analysis, identification, design and implementation. Laboratory work involves real-time identification and control of a range of electrical and electromechanical systems. Topics covered include:

• History of Control.
• Representation of linear dynamics and properties of systems.
• Time domain specifications of performance.
• Discrete-time systems and the Z-transform.
• Closed loop and open loop control. Classical PID controllers.
• Steady state errors and system type. Stability and robustness.
• Discrete-time systems and design by emulation.
• Root locus analysis and design of continuous and discrete systems.
• Frequency response of continuous and discrete time systems.
• Nyquist plots and stability margins.
• Lead-Lag control design.
• Sensitivity and robustness in the frequency domain.
• Practical design issues approaches.

Upon completion of this course, students will have the knowledge and skills to

1. Understand the properties of feedback and feed-forward control architecture and specify control architecture for a real world problem.
2. Understand the importance of performance, robustness and stability in control design.
3. Have a strong intuitive understanding of the link between the ODE representation, the s-domain representation and physical characteristics of the time response of an LTI SISO system.
4. Identify simple systems and dominant response characteristics from time domain step-response data.
5. Work confidently with block diagram representations of control systems.
6. Design PID controllers based on empirical tuning rules.
7. Understand system type and steady state tracking error analysis.
8. Compute stability of linear systems using the Routh array test and use this to generate control design constraints.
9. Sketch Evan's root locus diagrams by hand. Use Evan's root locus techniques is control design for real world systems. 
10. Understand and compute sensitivity and complimentary sensitivity for a feedback system.
11. Compute gain and phase margins, and understand implications for control, calculate the Nyquist conditions for a linear system and understand its implications in terms of robust stability margins, compute band-pass for a linear system and understand its significance in control design.
12. Design Lead-Lag compensators based on frequency data for an open-loop linear system.
13. Understand the state-space paradigm and models, and how to design state feedback controllers to achieve pole-placement.
14. Understand the basic structure of a sampled-data system, including a comprehension of issues such as Nyquist sampling theorem and aliasing as well as structure of Z-transform transfer functions and issues associated with inter-sample ripple, compute discrete-time equivalents of continuous-time plants using zero-order hold, trapezoid integration and pole matching techniques.

Problem Sheets (20%); Laboratories (25%); Tutorial attendance (5%); Final Exam (50%)

10 hours

MATH2305

Textbook:

• Franklin, G.F.et al Feedback Control of Dynamic Systems , 6th Edition, Prentice Hall, 2006

Alternatives to the main text are:

• Ogata, Modern Control Engineering , Prentice-Hall
• Franklin, Powell, Digital control systems
• Goodwin, Graebe, Salgado, Control system design

Course page http://eng.anu.edu.au/study/currentstudents/courses