Module information on this degree can be found below, separated by year of study.

The module information below applies for the current academic year. The academic year runs from August to July; the 'current year' switches over at the end of July.

Students select optional courses subject to rules specified in the Mechanical Engineering Student Handbook,  for example at most three Design and Business courses. Please note that numbers are limited on some optional courses and selection criteria will apply.

Advanced Control

Module aims

The principal aim of the module is to give the students understanding and working knowledge of modelling, analysis and design methods in relation to continuous and discrete control systems. Introduction to state variable analysis is also provided. It is assumed that the students have some knowledge of classical control theory, including frequency response methods and complex frequency methods. A level of understanding of linear algebra is also assumed. The coursework assignments are designed to give the student an opportunity to develop skills in carrying out realistic control designs using modern simulation and analysis tools.

ECTS units:  5

Learning outcomes

On successfully completing this module, students will be able to:

1. Explain the principles on which continuous and discrete-time control systems are modelled, analysed and designed 

2. Discuss the modelling and analysis of dynamics systems using state variable theory 

3. Analyse a continuous control system using Bode diagrams and Root Locus methods 

4. Design a closed-loop continuous control system for specified transient and steady state performance 

5. Develop discrete-time models of sampled data systems using the z-transform methods 

6. Perform stability analysis and closed loop control system design for sampled data systems system using Root Locus method in the z-domain 

7. Develop state variable models of linear dynamic systems

Module syllabus

    • Analogue control systems
    • Digital control systems
    • Introduction to state variable analysis
    • State variable models of continuous systems 
    • Introduction to Kalman filter

Teaching methods

Students will be introduced to the main topics through lectures, supported by technology (PowerPoint, Panapto and Blackboard). Short activities (using interactive pedagogies) will occasionally be introduced in the classroom setting to reinforce learning, for example through mentimeter and the like. You will be provided with problem solving sheets and should complete these as part of your independent study. Tutorials sessions will provide small group interaction with teaching staff where you are expected to engage in discussion on specific problems. 


Assessment details        
      Pass mark   
Grading method Numeric   50%
Assessment type Assessment description Weighting Pass mark Must pass?
Examination 3 Hour exam 100% 50% Y

Reading list

Module leaders

Dr Mihailo Ristic