Control Engineering

ENGINEERING & MANUFACTURING

Control Engineering

CONTROL ENGINEERING

Contents Why Cambridge Advance Online?

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Course summary

05

What you will learn on the course?

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The learning journey

08

Learning breakdown

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Course modules

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Meet your tutors

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Technical requirements

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Course certification

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We are delighted to offer this exciting programme of short online courses for professionals, giving you the opportunity to harness the latest research, innovation and thinking that the University of Cambridge has to offer.

Cambridge Advance Online brings together the academic strength of the University, and the publishing and assessment strengths of Cambridge University Press and Cambridge Assessment, allowing you to develop your skills and specialise in emerging areas that address global challenges.

Our certificated courses will reflect the Cambridge experience and values, with low student to tutor ratios and academically rigorous standards. They will allow you to engage directly with academics at Cambridge and are centred on rich interaction between students and subject experts. Each course will offer you the opportunity to join live sessions with academics and interact in collaborative exercises with learners worldwide.

The University of Cambridge is committed to supporting lifelong learning and, through Cambridge Advance Online, has invested in the latest education technology to provide professionals with the very best experience wherever they are in the world and at any stage of their career.

We look forward to welcoming you onto one of our courses and to our global community of learners.

Professor Graham Virgo

Senior Pro-Vice-Chancellor (Education)

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03 ENGINEERING & MANUFACTURING

Welcome to Control Engineering

Why Cambridge Advance Online?

CONTROL ENGINEERING

Welcome to Control Engineering

Control engineering is needed in all sectors of industry. It will be an essential enabling tool if we are to successfully meet environmental and climate change targets.

Whether it is battery management on an electric car, control of a smart grid with renewable generation, or production of chemicals in a hydrogen economy, advanced control engineering algorithms are going to be needed. We already make much use of control engineering in our manufacturing and process industries, in the aerospace and automotive industries, throughout the electronics and IT industries (in phones, games, internet routing) and increasingly in surgery and medical procedures, as well as in home automation.

This course is designed for graduate engineers from any engineering discipline who want to become more familiar with control engineering. We do not assume any specialist knowledge or skills in control and aim to give a good overview of the field, with corresponding skills and competencies. The course will familiarise you with modern software tools for modelling, simulation and analysis, of the type used in many industries.

Professor Jan Maciejowski Professor Emeritus of Control Engineering, University of Cambridge

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Timetable:

September | January | April | June

Subject area:

Engineering and Manufacturing

Format and length:

8 weeks | 6-10 hours per week

Price:

£1,800

Discover the what, when and why of control engineering. Learn to design and analyse control solutions.

Participants will learn to identify opportunities for feedback and control in their professional context and develop the skills needed to effectively use Matlab and Simulink to analyse and design control systems. They will look at performance specifications and theoretical limits on what can be achieved, as well as discuss sensors and actuators.

Although much of the course will centre on the basic workhorse control algorithm known as Proportional-Integral-Derivative (PID) control, participants will also go beyond PID control to explore ‘loop shaping’ and multivariable control, as well as some standard algorithms, including state feedback, linearquadratic optimal control, state observers and Kalman filters.

Relevant examples will be drawn from a range of applications to give context to conceptual information and participants will be encouraged to apply their learning to their own work through discussions and project work.

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Course summary

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What you will learn on the course?

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By the end of the course, participants will be able to: – Recognise needs and opportunities for control in their engineering projects or products.

– Assess which control method and technology is most appropriate to their project or product.

– Design and analyse a control solution.

– Model dynamic systems.

– Select and use appropriate software tools, including simulation software, to test, validate and iterate their control solutions.

Is this course right for you?

Key learning objectives

This course is aimed at the following roles in industry:

– Formulate a performance specification for a control system.

– Professional engineers faced with a control engineering problem who need to enhance their knowledge of the field

– Tune a PID controller.

– Managers who have control engineers working for them and who wish to better understand their job role – Individuals wanting to broaden their skill set to enhance their career opportunities

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– Gain an overview of multivariable control, optimal control and model predictive control.

– Appreciate state observers and Kalman filters.

– Understand the stability of a control system.

– Interpret Nyquist and Bode diagrams.

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The learning journey 09

Cambridge Advance Online courses are delivered over 6 to 8 consecutive weeks (dependent on the programme), with each week’s content following a clear, deliverable path to help facilitate learning.

Week 4

Week 5

Week 6

Orientation

You will get access to familiarise yourself with our learning platform, Canvas, start networking with peers and hear from your course leader.

Week 7*

Week 8* Week 1

Week 2

Week 3

*The duration of the programme is dependent on the course. Please check the course summary for information regarding course length.in your organisational context.

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Learning breakdown

Built content

Discussion

(e.g. videos, animations, quizzes, case studies, worked experiments)

1-2hrs

1hr

Research

(e.g. reading, looking for info online etc.)

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Live session

Week 3 explores Proportional-IntegralDerivative (PID) controllers and the motivation for each term. The content will explore the practical realisations of PID controllers as well as how to tune a PID controller, focusing on Ziegler-Nichols rules. There will be more systematic analysis and design and a discussion of Laplace transforms and transfer functions.

Students will create and manipulate models in these forms, using Matlab software and ’by hand’ exercises.

Performance, tuning, sensors and actuators

Module 4

PID controller, dynamical systems and transfer functions

1hrs

Week 1 contains examples of feedback control from history, from different domains and from participants’ own experience, and then looks at the use of block diagrams to represent systems. This is a discussion of why we use feedback and the ‘reduction of uncertainty’ formula S=1/(1+G), as well as the dangers of feedback and an introduction to Matlab and Simulink software. Participants will build simple feedback simulations themselves and explore instability and performance. The week will end with a look at feed forward control.

Module 2

Introduction to control systems

Module 3

5-6hrs

Module 1

Our online courses combine several different elements to create a balanced blend of learning. Participants will be able to learn at their own pace during the week, viewing content, engaging in discussions and completing any assignments. On average, our courses take 8 to 10 hours per week.

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Modelling, linearisation, stability

Week 2 looks at whether control of unmeasured variables is possible and how this can be done if a good model is available. There will be discussion of how to specify performance and unavoidable trade-offs. Participants will try trial-and-error tuning of simple control systems using Simulink and look at examples of sensors and actuators. Week 2 will also look at cascade structure and ask students to research how sensors and actuators work in their own industries.

Week 4 explains how we get the equations, from first-principles modelling, step-response experiments, other inputoutput tests, or operating records (using correlation analysis). Participants will learn why, for computer-based control, we need discrete-time models of systems.

There will also be a discussion on how to use linearising nonlinear models and when this is useful, as well as how to get frequency response from a model or from experiments. The week will also look at the stability of linear feedback systems: the Nyquist theorem, Bode plots, stability margins.

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Course modules

CONTROL ENGINEERING

Course modules

Meet your tutors

(Continued)

13 Week 5 shows students how to use Matlab and Simulink software to analyse and design a control system with a PID controller, aiming to achieve a given performance specification. Participants will also learn how to auto-tune a PID controller from scratch, without a model, and look at real-world actuator saturation. Week 5 will also discuss when PID is not enough to achieve the specification.

Week 7 will conduct a tour d’horizon (broad-but-shallow) scan of a number of topics that have not yet been treated in detail. This will include anti-aliasing filters for interfacing to the digital world as well as more general optimal control, including time-optimal bang-bang control.

Participants will be introduced to model predictive control, adaptive control and robust control.

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Module 8

Module 7

Horizon scan: what else is out there?

Module 6

Module 5

PID control continued

Beyond PID Week 6 looks at the options if a PID controller is insufficient to achieve the specification. The content will explore phase-lead and phase-lag compensators as well as multivariable control. Participants will consider state feedback and linearquadratic optimal control, state observers, Luenberger (reduced-order) observers and Kalman filters (non-statistical treatment).

Week 6 discusses the separation principle and participants will simulate and analyse a linear-quadratic-Gaussian feedback system to investigate the effects of disturbances and noise, and of parameter choices.

Major assignment Week 8 will contain a structured analysis and design exercise involving; formulating a performance specification; selecting and assessing a suitable control strategy; and designing and analysing a control system (possibly iteratively). This exercise will form the major assessed assignment at the end of the course. Participants will use Matlab and Simulink software. The problem may be based on the ’evaporator control’ project that has been used successfully in the third year of the Engineering Tripos at the University of Cambridge for many years, or it may be possible to use participants’ own workbased problems. The same problem will be introduced gradually in the assignments in earlier weeks, so that students will already have some familiarity with it.

Professor Jan Maciejowski Professor Emeritus of Control Engineering, University of Cambridge

Professor Jan Maciejowski was a Systems Engineer with Marconi Space and Defence Systems Ltd. From 1971 to 1974. At the University of Cambridge, he was a Professor of Control Engineering until November 2018, the Head of the Information Engineering Division from 2009 to 2014, and the President of Pembroke College from 2008 to 2018.

Jan was President of the European Union Control Association from 2003 to 2005, and President of the Institute of Measurement and Control for 2002.

He is a Chartered Engineer and a Fellow of the Institution of Engineering and Technology (IET), the Institute of Electrical and Electronic Engineers (IEEE), the Institute of Measurement and Control (InstMC), and of the International Federation of Automatic Control (IFAC). He was a Distinguished Lecturer of the IEEE Control Systems Society from 2001 to 2007.

Jan has consulted in the aerospace and process control sectors and has published two prize-winning graduate-level textbooks on control. Recently he has been working with economists on the optimal control of the Covid-19 pandemic.

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CONTROL ENGINEERING

14 Technical requirements

Course certification

– Sufficient internet speed and stability for video streaming (2 Mbps up/down)

You’ll be assessed using a range of modalities that emphasise real-world application of course material. On completion of your Cambridge Advance Online course, you will be eligible for a Certificate of Achievement and digital badge.

– Please see our recommendations on web browsers: https://bit.ly/2S4Qhh4

To get your Certificate you must achieve a minimum grade of 70% on course activities and your final tutor-marked project.

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If you have any questions or would like more information about our online courses, please contact our Enrolment Advisors at

advanceonlinesales@cambridge.org