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MSc Advanced Control and Systems Engineering / Course details
Year of entry: 2023
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Course unit details:
Applied Control
Unit code | EEEN60122 |
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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 |
Overview
BRIEF DESCRIPTION
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
Pre/co-requisites
Unit title | Unit code | Requirement type | Description |
---|---|---|---|
Nonlinear and Adaptive Control Systems | EEEN60111 | Pre-Requisite | Compulsory |
Robotics & Autonomous Systems | EEEN60115 | Pre-Requisite | Compulsory |
Aims
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 | |
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Independent study | 65 |
Teaching staff
Staff member | Role |
---|---|
Alexandru Stancu | Unit coordinator |
Farshad Arvin | Unit coordinator |