Due to Covid-19 students should refer to the module Blackboard pages for assessment details
|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%|
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.
The module aims to introduce the core concepts of control of engineering systems, building on experimental and numerical approaches from the year 2 module on Sensors, Electronics and Instrumentation. The mathematical and theoretical foundations needed to treat these concepts will be included.
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
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
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
|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