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The University of Southampton

ELEC6228 Applied Control Systems

Module Overview

This module will introduce the student to key topics within control and signal processing, developing understanding through a combination of theoretical content and practical application. The theoretical content is focussed in a number of key themes within the areas of system identification and control, encompassing fundamental theory together with application examples and case-studies. Emphasis is placed on guided background reading using supplied references and worked examples, to broaden and expand underlying knowledge, and enable students to apply it to practical situations. The second component of the module involves working in small groups to apply these techniques to real-world systems, and is supported through core material related to real-time hardware and the practical implementation of signal processing and control schemes. Each group will be given a practical control problem which will require design, implementation, and experimental evaluation of the theoretical approaches studied. This motivates and stimulates deep understanding of the theory through direct practical experience, and allows students to directly come into contact with and address issues related to real-world implementation. In the final component of the module, each group will present details of their practical work in a seminar to their peers, describing the experimental design process, additional theoretical content, implementation issues encountered, and the experimental results gained. This will enable them to critically evaluate the approaches of others.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • Elements involved in real-time control, including hardware, software and data transfer
  • Practical performance issues, performance criteria and iterative testing
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Derive models that capture the underlying characteristics of a practical problem
  • Express practical performance criteria in terms of control design specifications
  • Apply theoretical principles to derive control solutions to the problem
  • Apply advanced control methodologies to practical problems
  • Implement the controller in real-time
  • Interpret and refine solutions based on experimental test results
  • Assess the quality of the results in practice
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Work in a small team to solve a practical control problem
  • Write a report which describes the problem, and motivates the solution applied, and contains full detail of the application and validation of the proposed method
  • Present and explain theoretical solutions and practical results to the class
  • Critique other group’s work from theoretical and practical perspectives


The module is presented through fundamental material (“Introduction” and “Real-time implementation issues”), together with three core themes within Control and Identification. These three topics will operate in rotation from the six given below. The final component of the course will be seminars given by each group. Introduction - Review of control systems components, performance criteria and implementation issues - Overview of system identification methods, modelling for control, iterative testing and - Refinement - Choice of control structure, overview and comparison of control methodologies - Practical issues, software programming and hardware - Examples of practical systems, and control system implementation Real-time implementation issues - Overview of real-time commercial hardware, selection criteria and functionality - Noise reduction, signal conditioning, sampling, actuator limitations - Use of Matlab & Simulink and LabVIEW in real-time control - Guide to Real-time Workshop, tutorial and FAQs - Overview of report writing Optimal Control - Linear Quadratic Regulator: Problem Formulation - State Estimation - Solution Implementations - Introduction to the Minimum Principle - Linear Quadratic Tracking: Problem formulation - Solution Implementations - Practical applications and examples - References and further reading Model Predictive Control - Linear convex optimal control - Finite horizon approximation - Model predictive control - Fast MPC implementations - Practical applications and examples - References and further reading Iterative Learning Control - Motivation and application example - Frequency domain ILC - Time domain Iterative Learning Control - Extension for Nonlinear systems: Newton-based ILC - Non-minimum phase experimental example - Rehabilitation experimental example - References and further reading Data-driven Control - Model-based versus data-based control approaches - The data-driven approach - Identifiability and persistency of excitation - Solution of data-driven LQ finite-horizon control problem - Hankel matrix - Optimality of state feedback - Examples - References and further reading Adaptive control - Theadaptive control problem - Real-time parameter estimation - Self-tuning regulators - Model-reference adaptive control - Applications examples - Directed further reading Multivariable Control - Introduction to multivariable control - MIMO transfer functions, frequency response, relative gain array, RHP zeros - Introduction to MIMO robustness - Limitations on MIMO performance - Robust stability and performance analysis for MIMO systems - Controller designs (LQG, H2 and H∞ control) - Practical case studies - Directed further reading Student Seminars Each group writes a report detailing their work and present a seminar to the cohort, including: - How they have applied the theoretical aspects to their testbed in order to achieve the goals presented to them - How they tackled implementation issues - How they have used background reading to improve their designs - Evaluation of the experimental results achieved - Use of results to refine their designs - Practical demonstration - Question and answer session

Learning and Teaching

Preparation for scheduled sessions18
Wider reading or practice27
Completion of assessment task39
Follow-up work18
Total study time150



MethodPercentage contribution
Continuous Assessment 100%


MethodPercentage contribution
Set Task 100%


MethodPercentage contribution
Set Task 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisites: (ELEC3205 OR ELEC3206) OR ELEC6259

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