ACS230 Control Systems Design and Analysis

Module Description

This module gives a solid theoretical foundation for understanding feedback control system analysis, design and application and is suitable for general engineering students. This is supported by hardware laboratories, PC laboratory activities and coursework.

Content covers standard analysis tools such as root-loci, Bode diagrams, Nyquist diagrams and z-transforms. The latter part of the course focuses on the design of common feedback strategies using these analysis tools and students will undertake indicative designs and reinforce learning through application to laboratory and hardware systems.

Credits: 20 (Academic Year)

Module Leader

Dr Mahdi Mahfouf
Amy Johnson Building

If you have any questions about the module please talk to us during the lectures or labs in the first instance. It is likely that other students will learn from any questions you ask as well, so don’t be afraid to ask questions.

Outside of lectures please contact us via the Blackboard (MOLE) discussions board as this ensures all students see the query and response.

Other teaching staff

Dr Mahdieh Sadat Sad Abadi

Ben Taylor

Learning Outcomes

Learning Outcomes

By the end of the module students will be able to:

  1. Explain the principles of closed-loop control, transfer function models, stability and time response analysis, for continuous and discrete domain systems. [SM1p, SM2m, SM3p]
  2. Interpret practical performance specifications of a control system and convert specifications from one format to another, for continuous and discrete domain systems. [EA2m, EA3p]
  3. Analyse, design and contrast linear closed-loop systems using classical and modern control techniques and compensator structures, for continuous and discrete domain systems. [EA1m, EA2m, D4p]
  4. Use industry standard software for control system analysis and design in the continuous as well as discrete time domain. [EP3m]
  5. Implement and evaluate different compensator strategies on laboratory equipment. [EP1p, EP3p, D1p, D3p]
  6. Appreciate the importance and integral role of digitisation in modern technologies from the viewpoint of systematic manipulation of information, including industrial & life sciences applications as well as research, and get to grips with the general idea behind digital systems, their pros and cons, as well as the constraints relating to their implementations across sectors. [EA4p]
  7. Understand the theory of information by highlighting how the optimal selection of the sampling interval helps avoid ‘aliasing’, and explain how this methodology, combined with the appropriate use of digital hardware and interfacing, can help avoid loss of information in modelling (including system identification), digital signal processing, and digital control. [EA1m]
  8. Assess the hardware and software requirements to realise digital as well as hybrid (analogue and digital) loops in off-line and real-time modes for acquiring open/closed loop data, analyse the data in the digital domain using the appropriate mathematical tools and design and implement digital control solutions to achieve performance criteria that include stability as well as economic factors (e.g. energy savings). [EA2m, EA3m, EA4m, ET2p, D1m]

This module satisfies the AHEP3 (Accreditation of Higher Education Programmes, Third Edition) Learning Outcomes that are listed in brackets after each learning outcome above. For further details on AHEP3 Learning Outcomes, see the downloads section of our accreditation webpage.



1. Explain the principles of closed-loop control, transfer function models, stability and time response analysis;

2. Interpret practical performance specifications of a control system;

3. Analyse a simple system using the root locus method;

4. Design a simple control law using the root locus method.

5. Analyse a simple control systems using different forms of frequency response diagrams;

6. Use computer aided design software for control system analysis and design;

7. Convert time-domain design specifications into frequency domain design specifications.

8. Analyse and design common compensator structures (e.g. lead, lag) using frequency response methods.

9. Implement and evaluate different compensator strategies on CAD tools and laboratory hardware.

10. Demonstrate the application of control design tools in real applications.

11. Understand the need for the digitisation of systems as well as understand the idea behind digital systems;

12. Understand the Shannon-Nyquist Theorem and be able to select the sampling interval for a given system;

13. Determine the z-transform and its inverse for a given system and get to grips with the concept of mapping between Laplace and z domains;

14. Manipulate and understand the algebra associated with sampled system diagrams;

15. Analyse and compensate for sampled-data systems using Bode diagrams and the root-locus technique.

Teaching Methods

Learning and Teaching Methods

NOTE: This summary of teaching methods is representative of a normal Semester. Owing to the ongoing disruption from Covid-19, the exact method of delivery will be different in 2020/21.

Lectures: 48 hours
Tutorials: 20 hours
Laboratory Sessions: 6 hours
Independent study: 120 hours

Teaching Materials

Learning and Teaching Materials

All teaching materials will be available via MOLE and a university shared server (accessible via MUSE and on the main network).



    Semester 1 Mid Term Quizzes (20%)

    Semester 1 Lab Work (5%)

    Semester 1 Exam (25%)

    Semester 2 Mid Term Quiz (15%)

    Semester 2 Lab Work (10%)

    Semester 2 Exam (25%)



All the semester 1 assignments are designed to give students fast quantitative feedback on their progress in that they allow students to assess explicitly to what extent they have mastered different topics. These are delivered via MOLE computer quizzes.

In addition, formative drop in sessions are available several hours per week in semester 1 for students to develop any MATLAB skills required for some of the quizzes and indeed to ask queries on tutorial sheets. Demonstrators will also answer other queries related to the module. Students can ask for feedback on their progress and raise any other concerns as well as seek more detailed feedback on any assignments. The lecturers are also responsive to requests for some generic feedback during lecture time, as time permits.

Student Evaluation

Student Evaluation

Students are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of the module.

You can view the latest Department response to the survey feedback here.

Recommended Reading

Recommended Reading

Primary Texts:

  • Dorf, R.C and Bishop, R.H, 2011, Modern Control systems, 12th Edition Addison-Wesley [available in Information Commons, 629.8312 (D)]
  • Ogata, K, 2010, Modern control engineering, 5th Edition, Prentice Hall, ISBN 0-13-261389 [available in Information Commons, 629.8 (O)]
  • Golnaraghi, F and Kuo, B.C, 2008, Automatic control systems (9th edition), Prentice Hall, 13 978 0470 04896 2 [available in Information Commons, 629.831 (G)]
  • Wilkie J; Johnson M and Katebi R, 2002, Control Engineering: an Introductory Course, Palgrave, ISBN 0-333-77129-X [available in Information Commons, 629.8 (W)]
  • Nise, N.S, 2011, Control systems engineering (5th edition), Wiley, [available in Information Commons & St. George’s Library, 629.8 (N)]

Secondary Texts:

  • Matko, D., Karba, R. and Zupancic, B., 1992, Simulation and modelling of continuous systems: a case study approach, Prentice-Hall
  • Control Engineering - An introduction with the use of Matlab ( ) e-book by D.P. Atherton, ISBN 978-87-7681-466-3