Master of Engineering (MEng)

MEng Mechatronic Engineering

*This course is now closed for applications for 2025 entry.

  • Duration: 4 years
  • Year of entry: 2025
  • UCAS course code: HHH6 / Institution code: M20
  • Key features:
  • Scholarships available
  • Accredited course

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Fees and funding

Fees

Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £34,000 per annum. For general information please see the undergraduate finance pages.

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Scholarships/sponsorships

The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.

For information about scholarships and bursaries please visit our undergraduate student finance pages and our Department funding pages .

Course unit details:
Numerical Analysis

Course unit fact file
Unit code EEEN30101
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 1
Available as a free choice unit? No

Overview

Brief description of the unit:

The unit gives an introduction to numerical methods that are routinely used by engineers in analysis and design.

Topics will include: root finding and optimization; solving linear algebraic systems; curve fitting; numerical integration and differentiation; numerical solutions of simple ordinary differential equations and partial differential equations.

There will be an emphasis on numerical accuracy, numerical stability and computational efficiency.  Meanwhile the techniques will be illustrated on examples from the Electrical and Electronic Engineering, Electronic Engineering and Mechatronic Engineering streams.  These will include: circuit analysis, power flow optimization; digital signal processing; plotting V/I characteristics; finding transfer function poles; realizing transfer function responses.

Lecture material will be illustrated with Matlab examples.  Students are encouraged to implement the techniques on other software platforms.

Pre/co-requisites

Unit title Unit code Requirement type Description
Signals and Systems EEEN20131 Pre-Requisite Compulsory
Mathematics 2E1 MATH29681 Pre-Requisite Compulsory

Aims

The course unit unit aims to: Reinforce students' confidence in using Matlab and other software platforms suitable for numerical analysis. Give an overview of numerical methods routinely used by electrical, electronic and mechatronic engineers. Illustrate their application on examples encountered in other 1st, 2nd and 3rd year units.

Learning outcomes

On the successful completion of the course, students will be able to:

ILO 1: Calculate numerical solutions to integration problems and the time evolution of simple dynamical systems

ILO 2: Code simple algorithms for root finding, LU decomposition and least squares

ILO 3: Solve simple line fitting and optimization problems

ILO 4: Explain the role of randomisation for non-convex optimisation problems

ILO 5: Analyse numerical accuracy in the context of floating point arithmetic and determine suitable stopping criteria for numerical computation

ILO 6: Factorize matrices and interpret their rank, condition number and singular values in terms of linear algebraic equations modelling physical applications

ILO 7: Write code for numerically efficient matrix computation

Teaching and learning methods

Standard lecture and laboratory format, but with an emphasis on numerical examples and applications.

 

Assessment methods

Method Weight
Other 20%
Written exam 80%

Coursework

Coursework forms 20% of the unit assessment

Assignments related to both the laboratory sessions

Feedback methods

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Recommended reading

S C Chapra. Applied Numerical Methods with MATLAB for Engineers and Scientists, 3rd edition, McGraw-Hill 2012

Study hours

Scheduled activity hours
Lectures 12
Practical classes & workshops 3
Tutorials 12
Independent study hours
Independent study 73

Teaching staff

Staff member Role
Sareh Malekpour Unit coordinator
Zhenhong Li Unit coordinator

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