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MSc Advanced Control and Systems Engineering with Extended Research / Course details

Year of entry: 2020

Course unit details:
Process Control & Model Predictive Control

Unit code EEEN60112
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by Department of Electrical & Electronic Engineering
Available as a free choice unit? No


Description of unit:

(1) Process Control:

PID control: purpose of the three terms, implementation in industry

PID tuning, comparing methods such as Ziegler-Nichols/Cohen-Coon with lambda-tuning

Velocity and positional form of discrete PID

Cascade control, decoupling (static and dynamic), Smith predictors

Relative Gain Array

(2) Advanced Process Control - Model Predictive Control

MPC control formulation (general characteristics of MPC formulation, translation of MPC problem into quadratic programming optimisation problem, constant output disturbance observer model, infeasibility and softening of the constraints)

Practical considerations (empirical model development, usage of design/tuning parameters, implementation/commissioning of MPC)

(3) Real-time optimisation (linear programming)

(4) Case studies:

Design of a control system for a typical CSTR chemical reactor as well as distillation column



Unit title Unit code Requirement type Description
Control Fundamentals EEEN60108 Pre-Requisite Compulsory
State-Space and Multivariable Control EEEN60109 Pre-Requisite Compulsory


The course unit aims to:

  •  Introduce students to the fundamental concepts of applied industrial process control, including cascade, feedforward control and decouplers.
  •  Introduce students to the formulation as well as the main implementation details regarding Model Predictive Control (MPC) as well as real-time optimisation.


Learning outcomes

Knowledge and understanding

  • Understand the tools and methods used in industrial process control

Intellectual skills

  • Design various process controllers, including single-loop PID, cascade, feedforward, de-couplers and model predictive control.

  • Explain what model predictive control is and how it is applied to multivariable problems
  • Explain the concept of real-time optimisation and solve a linear programming problem using graphical methods


Practical skills

  • Tune a PID controller using various tuning rules
  • Tune MPC controller by selecting values of weights in the corresponding cost function.

Transferable skills and personal qualities

  • Use the relevant modelling and design tools for application in other areas.
  • Use computer based simulation tools to analyse the response of dynamic systems

Assessment methods

Method Weight
Other 20%
Written exam 80%

Written Examination

Four questions, answer all questions

Length of examination: 3 hours

Calculators are permitted

The examination forms 80% of the total unit assessment

Duration: 3 hours


The number of laboratories: 2

The length of each laboratory: 3 hours

 Laboratory is assessed by a short report

Each piece of coursework is worth 10%



Study hours

Scheduled activity hours
Lectures 27
Practical classes & workshops 6
Tutorials 9
Independent study hours
Independent study 108

Teaching staff

Staff member Role
Barry Lennox Unit coordinator
Ognjen Marjanovic Unit coordinator

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