Control M ENG5022
- Academic Session: 2020-21
- School: School of Engineering
- Credits: 20
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 1
- Available to Visiting Students: Yes
This course provides a theoretical background to classical control and shows how it is applied to real systems. Topics include frequency-domain and time-domain methods, multi-variable and state-space techniques, analogue control hardware, digital signal processing, and the use of digital embedded systems for control. A laboratory and an assignment give the opportunity to apply the methods practically.
4 lectures per week
Control 4 (ENG4042)
Aerospace Control I (ENG5008)
90% Written Exam
5% Written Assignment: report on controller design
5% Report: laboratory report
Main Assessment In: December
This aims of this course are to:
■ provide an understanding of continuous and discrete time control systems;
■ develop linear control systems in the state space and in the frequency domains;
■ introduce multi-variable control methods;
■ set the theory in a practical context by introducing signal processing concepts in the context of digital control and providing techniques for digital control design and implementation in modern digital microcontrollers.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
■ explain frequency domain, time domain and state space concepts of control systems;
■ use frequency domain design and analysis techniques, including Bode plots, Nyquist diagrams and the root locus method;
■ analyse and design feedback controllers using proportional, integral and derivative (PID) control and pole placement;
■ appreciate the use of MATLAB and Simulink as simulation tools for control system analysis and design;
■ represent continuous and discrete dynamic systems in state space form;
■ implement multi-variable control strategies;
■ model a servo motor system and design, analyse and experimentally evaluate proportional feedback control;
■ explain the basic concepts of digital control;
■ use the z-transform, perform signal analysis and identify the dynamic response of discrete signals;
■ describe the phenomenon of aliasing in sampled data systems, its effects and how to avoid it;
■ design discrete equivalent of continuous controllers by emulation, using different techniques.
Minimum Requirement for Award of Credits
Students must attend the degree examination and submit at least 75% by weight of the other components of the course's summative assessment.
Students must attend the timetabled laboratory classes.
Students should attend at least 75% of the timetabled classes of the course.
Note that these are minimum requirements: good students will achieve far higher participation/submission rates. Any student who misses an assessment or a significant number of classes because of illness or other good cause should report this by completing a MyCampus absence report.