MSc Advanced Control and Systems Engineering / Course details

Year of entry: 2023

Course unit details:
Applied Control

Course unit fact file
Unit code EEEN60122
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Offered by Department of Electrical & Electronic Engineering
Available as a free choice unit? No



LabVIEW Fundamentals – Core 1 and Core 2. This component of the unit is taught using in-laboratory instruction and structured exercises, with in-laboratory assessment of achievement:

Introduction to the LabVIEW development environment      

Fundamental programming concepts in LabVIEW

Debugging and error handling in LabVIEW

Building graphical interfaces and presenting data

Accessing analogue and digital hardware interfaces

Control applications using LabVIEW and mobile robots

Structured LabVIEW programming techniques; and Real-time programming


Advanced control for mobile robots:

Sensors and coordinate systems for mobile robots

Locomotion for mobile robots – modelling, kinematics, dynamics, actuator control

From path-planning to trajectory generation – The essential link between advanced control and autonomy in Autonomous Systems field

Trajectory generation algorithms

Introduction to advanced control for mobile robots: path following and trajectory tracking

Advanced control for long term navigation

Applications using real mobile robots


Unit title Unit code Requirement type Description
Nonlinear and Adaptive Control Systems EEEN60111 Pre-Requisite Compulsory
Robotics & Autonomous Systems EEEN60115 Pre-Requisite Compulsory


This course unit detail provides the framework for delivery in 2020/21 and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.

The unit aims to:

Provide students with necessary skills to build and control their own mobile robot.

Provide students with understanding of LabVIEW programming (Core 1 & Core 2).

Enable the students to design advanced control strategies for mobile robots.

Provide students with an overview on the link between advanced control and autonomy in autonomous systems field.

Enable students to design trajectory generation algorithms for long term navigation for mobile robots.

Learning outcomes

Knowledge and understanding

  • Demonstrate skills in LabVIEW programing
  • Demonstrate understanding of mobile robots – modelling and advanced control
  • Demonstrate understanding of algorithms for trajectory generation

Intellectual skills

  • Use advanced control strategies for mobile robots navigation
  • To understand the link between advanced control and autonomy in Autonomous Systems field

Practical skills

  • To build a mobile robot
  • Advanced control for mobile robots
  • LabVIEW programing

Transferable skills and personal qualities

  • Students achieving a distinction mark in the unseen written examination will be able to take an extra examination to become Certified LabVIEW Academy Developers (CLAD). This gives them an extra qualification and enhances their CV
  • Students can participate with their designed mobile robot to a robotic competition organised by the School of Electrical and Electronic Engineering.
  • Use LabVIEW to control mobile robots
  • Apply mobile robots techniques to other control related problems

Assessment methods

Method Weight
Other 30%
Written exam 70%

Written Examination

The examination forms 50% of the total unit assessment

Practical Examination

Scheduled during the last week of the unit (week 12)

This examination forms 20% of the unit assessment 

Course Work

Lab and Assignment 1: Trajectory generation for mobile robots - The link between advanced control and autonomy

Submission date: A report based in the lab must be submitted on Sunday, Week 11, Semester 2

Maximum mark for assignment 1 forms 15% of the overall unit mark

Lab and Assignment 2: Advanced control methods for mobile robots

Submission date: A report based on the course work must be submitted on Sunday, Week 12, Semester 2      

Maximum mark for assignment 2 forms 15% of the overall unit mark

Feedback methods


Study hours

Scheduled activity hours
Lectures 13
Practical classes & workshops 50
Supervised time in studio/wksp 10
Tutorials 12
Independent study hours
Independent study 65

Teaching staff

Staff member Role
Alexandru Stancu Unit coordinator
Farshad Arvin Unit coordinator

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