Electronic Engineering - with Industrial Experience (5 Years) [MEng]
View content for printing (opens a new page)EEEN30002 - Engineering Analysis
Availability - Course (Compulsory/Elective)
Requisites
| Pre Requisites | |
| EEEN20027 Signals And Systems | |
| EEEN20030 Control Systems 1 | |
| 1st and 2nd Year Mathematics | |
Aims
The programme unit aims to:
- Introduce state space models, and probabilistic methods of signal and systems analysis.
- To link probabilistic methods and frequency and time domain approaches to comprehensive system analysis in preparation for courses in Real Time Systems, Linear Optimal Control, Nonlinear Control Systems, and Multimedia Communications
Brief Description
This unit will cover the following:
This unit will introduce two subjects that are important in communications and control
engineering: state space models, and probabilistic methods of signal and systems analysis. All concepts will be illustrated with examples and students will do coursework and exercises using BlackBoard and Matlab.
State Space Models: linear state space models from differential equations; relationship
between state space models and transfer functions; dynamic response of state space models; similarity transformations and choice of basis; numerical issues, well-conditioned and ill-conditioned realisations.
Probabilistic Methods: the concept of probability; random variables, distribution, pdf correlation functions; spectral density; response of linear systems to random inputs.
Learning Outcomes
Students will be able to:
Knowledge and understanding:
- Describe simple electrical systems in mathematical terms using state differential equations and state space representations;
- Identify the principal features of linear system time response;
- Define terms such as eigenvalue, eigenvector, transfer function, system state matrix, system observability and controllability.
- Describe signals and systems using probabilistic methods.
- Understand the concepts of probability; random variables, distribution, probability density function, and correlation functions.
Intellectual Skills:
- Assess system small disturbance stability, time response, controllabilty and observability.
- Derive expressions for transfer function from state space representation and state space representation from differential equations and transfer functions;
- Derive canonical form of the system from the state space representation and vice versa applying basic changes and transformations;
- Evaluate the parameters of random processes and process them through linear systems;
- Derive the probability density function;
- Determine the response of linear systems to random inputs.
Practical skills:
- Analyse continuouse linear system's time response, small disturbance stability, controllability and observability.
- Analyse random signals and the response of linear systems to random signals;
- Use Matlab to perform these calculations.
Transferable skills and personal qualities:
- Development of a critical attitude in the assessment of analytical results.
- Encouragement of physical interpretation where possible.
- Development of capability in problem solving using mathematical models.
Teaching & Learning Process (Hours Allocated To)
Lectures |
Tutorials/Example Classes |
Practical Work/Laboratory |
Private Study |
Total |
|---|---|---|---|---|
| 20 | 4 | 4 | 72 | 100 |
Assessments
Unseen Written Examination:
Four questions, answer all questions
Duration: 2 hours
Calculators are permitted
This examination forms 80% of the unit assessment
Coursework 1:
Blackboard coursework assignment (state-space analysis)
Duration: 2 hours
Deadline: Week 6, Semester 1
Coursework 1 forms 10% of the unit assessment
Coursework 2:
Blackboard coursework assignment (probabilistic analysis)
Duration: 2 hours
Deadline: Week 11, Semester 1
Coursework 2 forms 10% of the unit assessment
Staff Involved
| Dr Alexander Lanzon | - | Lecturer |