Module Information

Module Identifier
Module Title
Engineering Control Theory
Academic Year
Semester 1
Reading List
Other Staff

Course Delivery



Assessment Type Assessment length / details Proportion
Semester Assessment Written Report  : two elements weighted at 15% each  30%
Semester Exam 2 Hours   Written examination  70%
Supplementary Exam 2 Hours   Written Examination  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. Determine transfer functions for simple models, and extract dynamic behavior, apply root-locus/ frequency domain analysis, design controllers for simple plants.
2. Critically evaluate performance/stability of these models using the techniques in 1.
3. Illustrate the differences between open loop vs. closed loop strategies, summarize the potential advantages from use of feedback.
4. Practical skills: gain a familiarity of control system design and analysis, and utilize the foundational mathematical, theoretical and numerical methods to analyze and implement these control principles.
5. Summarize the effect of noise degradation on systems, and resolve the problem in specific cases.

Brief description

The module aims to introduce the core concepts of control of engineering systems, building on experimental and numerical approaches. The mathematical and theoretical foundations needed to treat these concepts will be included.


Basic Electronics (Theoretical Formulation)
Kirchhoff's Circuit Laws, impedances, voltage dividers, difference measurements and bridges (Wheatstone, Maxwell, etc.)
Basic filters: PID filters
Operational amplifiers, inverting amplifiers, current-to-voltage converters, differential amplifiers

Control Systems
Open and closed loop, feedback systems, PID control
Process controllers, input-state-output models

Engineering Systems Theory
Block design, gain, transfer functions, feedback, sensitivity analysis,
disturbance rejection, stability analysis, Nyquist and Bode diagrams
Kalman decomposition: controllability/ observability, stabilizability, detectability

Signal Processing
Circuits as PID filters
Analogue to digital conversion, Shannon Sampling Theorem, aliasing
Noise: Gaussian, shot noise, flicker (1/f) noise

Filtering in the Presence of Noise: the Kalman Filter

Module Skills

Skills Type Skills details
Application of Number Throughout the module.
Problem solving Throughout the module.
Subject Specific Skills Engineering and control theoretic principles. Developed throughout the module.


This module is at CQFW Level 6