CONTROL ENGINEERING - 2023/4
Module code: EEE3005
Expected prior learning: Module EEE2033 – Electronics III: Circuits, Control and Communications or equivalent learning.
Module purpose: Control Engineering covers classical control theory as well as more modern methods. Students have the opportunity in this module to evaluate and apply various control techniques. This module builds on basic concepts previously introduced in Electronics III: Circuits, Control and Communications EEE2033, or equivalent learning and builds the fundamentals for a subsequent career as a control engineer or systems engineer.
Computer Science and Electronic Eng
JAYAWARDENA Imalka (CS & EE)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 6
JACs code: H660
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 94
Lecture Hours: 11
Tutorial Hours: 11
Guided Learning: 10
Captured Content: 24
Prerequisites / Co-requisites
- Introduction to closed-loop control principles. System modelling in time and complex frequency domains. Review of Laplace Transforms. Initial and final value theorems. Differential equations, transfer functions and block diagram manipulation. Multi-loop systems with secondary inputs and outputs and signal flow graphs. Relationship between pole-zero patterns and system impulse response. Stability in time and complex frequency domains. Proportional, integral and derivative control.
- Routh's stability criterion. Poles-zeros, and root locus concept. Loop gain and other parameters. Guidelines for sketching root locus. Zero-degree root loci. Lead and lag compensation. Frequency response method. Polar and Bode plots and guidelines for sketching. Nyquist stability criterion and its application. Relative stability. Nichols chart and its application. Specification of system performance. Steady state accuracy, system type and error constants. Lead/lag compensation, theory and design. Controller design for systems with time delay.
- Multivariable analysis. State space representation and advantages. Controllability and observability. Pole placement controller design techniques, based on state variable feedback. Estimator design. Lyapunov stability.
- Introduction to digital control. Modelling sampled-data systems. Z-transform analysis. Pulsed transfer functions. Stability, steady state accuracy and transient response in the Z-domain. Methods of design of digital control systems for specified performance.
|Assessment type||Unit of assessment||Weighting|
|Examination Online||ONLINE (OPEN BOOK) EXAM WITHIN 4HR WINDOW||80|
The assessment strategy is designed to provide students with the opportunity to demonstrate the learning outcomes. The assignment will assess the ability to learn about practical design of control systems.
Thus, the summative assessment for this module consists of:
- Assignment report due in week 9
- Online open book examination within 4 hour window
Any deadline given here is indicative. For confirmation of exact date and time, please check the Departmental assessment calendar issued to you.
Formative assessment and feedback
For the module, students will receive formative assessment/feedback in the following ways.
· During face-to-face sessions, by question and answer sessions·
· By means of unassessed tutorial problem sheets (with answers/model solutions)
· Via the marking of written reports
· Via assessed coursework
- Students will have the knowledge to understand control system analysis and design, including state-space and sampled-data analysis, and to apply the techniques to a practical problem using Matlab.
- The module also aims to provide opportunities for students to learn about the Surrey Pillars listed below.
|001||Model physical systems and use mathematical tools, such as Laplace and Z transforms, transfer functions and block diagrams to analyse/design single input/output control systems.||KCT||C1, C3|
|002||Understand pole-zero diagrams and assess stability using Routh, Nyquist, Bode plots, Root-locus.||KC||C2|
|003||Specify systems in terms of time/frequency and other performance criteria, and design compensators using Root-locus, Bode plots and Nichols charts.||KC||C6|
|004||Analyse systems using state-space representation.||KC||C2|
|005||Assess stability, response and steady-state errors for sample-data systems and apply to simple design examples.||KCT||C3|
|006||Report in written form the outcome of individual or group based courseware using MATLAB||PT||C16, C17|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to achieve the following aims:
The strategy is designed to give students an understanding of basic concepts in control engineering, and also to learn how to analyse and model control systems using MATLAB.
Learning and teaching methods include the following:
- Online pre-recorded lecture content supported with face-to-face in class problem solving sessions. Sessions will employ a flipped class approach in which students attempt problems beforehand and then discuss their solution in class.
- Coursework: Report on a tutorial sheet that requires use of MATLAB modelling software (alternative assignment is literature-based survey report).
- Tutorial presentation in class.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: EEE3005
This module trains the student on the use of advanced control engineering concepts with a key focus on designing systems for realising different performance/response criteria. The module will also train the student on the use of MATLAB as a tool for problem solving in Control Engineering which will improve their Digital Capabilities and bring the final skills attained in line with current industrial expectations. Further, the Resourcefulness and resilience of students will be improved based on a number of challenges/problems which will be given to solve in groups or individually throughout the semester. The above characteristics taken together is expected to improve the Employability of students who will be taking up this module and aiming to build their careers as Control Engineers or System Designers. While Sustainability is less likely to be addressed during this course, the concepts learnt during this module are applicable for sustainable practices.
Programmes this module appears in
|Electrical and Electronic Engineering MEng||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering MEng||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering with Space Systems MEng||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering with Nanotechnology MEng||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering with Computer Systems MEng||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering BEng (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering with Computer Systems BEng (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering with Nanotechnology BEng (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electronic Engineering with Space Systems BEng (Hons)||2||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Electrical and Electronic Engineering BEng (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.