ENGN3223: Control Systems

Control systems, or more precisely feedback control system, is fundamental in most engineering disciplines such as electrical, mechanical and chemical engineering. Biological system is a good example of this control theory and thus our sociaty and economy are also governed by this law. There are many good references on the web, so have a look at:

Classical control theory, based on transfer function, was mostly developed during the first 60s of the twentieth centrury, but is still popular in industries!. The classical controller design is iterative from the insights. The design tools are root locus, Bode plot and Nyquist plot which provide cause-and-effect relationships from the controller modification and system performance.

During this coursework, you will learn about the basic principles of (negative) feedback system, and how to design real-time controllers for electrical circuits and temperature regulating system. The three elements in this course are

Analysis
- Introduction to Control .
- Dynamic Response of Systems (Transfer function and Laplace Transfrom)
- Basic Properties of Feedback (closed-loop response)
- Sampled Data Systems (Z-Transfrom)
Design
- Time domain Design (PID control, meeting rise-time, overshoot, steady-state error etc)
- Root locus Design (change open-loop gains and predict closed-loop response)
- Frequency Response Design (Bode and Nyquist plots, robustness from margins)
Implementation
- Real-time Workship and Simulink-based Implementation

The course outline used in last semester is available [ENGN3223-CourseOutline.pdf].

Textbook: Franklin, et al.(2006), Feedback Control of Dynamic Systems, 5th edition, Prentice Hall

Note that Modern control theory, based on state-space model, is not covered in this course. This provides more systematic design method for MIMO (multi-input and multi-ouput) system and complex system. There are also many branches here such as optimal control (coupled with optimal estimation as Kalman filter, model-predictive control), adaptive control, nonlinear control, robust control and so on. Which control theory to use really depends on your application and specification.