Undergraduate Teaching 2025-26

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Engineering Tripos Part IIB, 4F2: Robust and Nonlinear Control, 2022-23

Module Leader

Dr F Forni

Lecturers

Dr F Forni and Prof R Sepulchre

Timing and Structure

Lent term. 14 lectures + 2 computer lab sessions. Assessment: 100% coursework

Prerequisites

3F2 assumed.

Aims

The aims of the course are to:

  • introduce fundamental concepts from nonlinear dynamic systems
  • introduce techniques for the analysis and control of nonlinear and multivariable systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • apply standard analysis and design tools to multivariable and nonlinear feedback systems.
  • appreciate the diversity of phenomena in nonlinear systems.

Content

Part I. ROBUST CONTROL (7L + 1 Computer Lab session, Dr F Forni)

1. Uncertainty and Nonlinearity in control systems: simple models.

2. Signal spaces and system gains.

3. The small-gain theorem and the passivity theorem. Phase versus gain uncertainties

4. Dissipativity theory

5. Robust stability and performance. Stability margins.

6. An introduction to H-infty control. 

7. Gap metrics

PART 2: NONLINEAR SYSTEMS (7L + 1 computer lab session, Dr F Forni)

1. Small and large signal analysis. Contractive systems. Fading memory operators.

2. State-space analysis and Nyquist. Differential stability. Differential dissipativity. Differential circle criterion.

3. Feedback systems: simple models.

4. Phase portrait analysis.

5. Analysis and design of switches and clocks. Robust differential control.

6. Monotone systems. Contraction of cones. Polyhedral cones. Applications in biology.

7. Describing function analysis.

Further notes

ASSESSMENT

Coursework only.

Coursework

Coursework Format

Due date

& marks

[Coursework activity #1  Robust control of haptic interfaces

Coursework 1 brief description

Learning objective:

  • Learn how to model uncertainty in an engineering application
  • Design a robust controller in Matlab

Individual Report 

  anonymously marked

 

24 February 2023

[30/60]

[Coursework activity #2  Feedback oscillations control ]

Coursework 2 brief description

Learning objective:

  • Learn how to model and analyse nonlinear oscillations in feedback systems
  • Design a nonlinear oscillator in a biologically motivated appication

Individual Report

anonymously marked

  24 March 2023

[30/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 16/01/2023 15:45

Engineering Tripos Part IIB, 4F2: Robust and Nonlinear Control, 2023-24

Module Leader

Prof F Forni

Lecturer

Prof F Forni

Lecturer

Dr T Chaffey

Timing and Structure

Lent term. 14 lectures + 2 computer lab sessions. Assessment: 100% coursework

Prerequisites

3F2 assumed.

Aims

The aims of the course are to:

  • introduce fundamental concepts from nonlinear dynamic systems
  • introduce techniques for the analysis and control of nonlinear and multivariable systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • apply standard analysis and design tools to multivariable and nonlinear feedback systems.
  • appreciate the diversity of phenomena in nonlinear systems.

Content

Part I. ROBUST CONTROL (7L + 1 Computer Lab session, Prof F Forni)

1. Uncertainty and Nonlinearity in control systems: simple models.

2. Signal spaces and system gains.

3. The small-gain theorem and the passivity theorem. Phase versus gain uncertainties

4. Dissipativity theory

5. Robust stability and performance. Stability margins.

6. An introduction to H-infty control. 

7. Gap metrics

PART 2: NONLINEAR SYSTEMS (7L + 1 computer lab session, Prof F Forni and Dr T Chaffey)

1. Small and large signal analysis. Contractive systems. Fading memory operators.

2. State-space analysis and Nyquist. Differential stability. Differential dissipativity. Differential circle criterion.

3. Feedback systems: simple models.

4. Phase portrait analysis.

5. Analysis and design of switches and clocks. Robust differential control.

6. Monotone systems. Scale relative graphs (SRGs). Applications in biology.

7. Describing function analysis.

Further notes

ASSESSMENT

Coursework only.

Coursework

Coursework Format

Due date

& marks

[Coursework activity #1  Robust control of haptic interfaces

Coursework 1 brief description

Learning objective:

  • Learn how to model uncertainty in an engineering application
  • Design a robust controller in Matlab

Individual Report 

  anonymously marked

 

23 February 2024

[30/60]

[Coursework activity #2  Feedback oscillations control ]

Coursework 2 brief description

Learning objective:

  • Learn how to model and analyse nonlinear oscillations in feedback systems
  • Design a nonlinear oscillator in a biologically motivated appication

Individual Report

anonymously marked

  22 March 2024

[30/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 04/01/2024 15:40

Engineering Tripos Part IIB, 4F2: Robust & Nonlinear Systems & Control, 2017-18

Module Leader

Dr F Forni

Lecturers

Dr F Forni and Dr I Lestas

Timing and Structure

Lent term. 14 lectures + 2 examples classes. Assessment: Exam only

Prerequisites

3F2 assumed.

Aims

The aims of the course are to:

  • introduce fundamental concepts from nonlinear dynamic systems
  • introduce techniques for the analysis and control of nonlinear and multivariable systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • apply standard analysis and design tools to multivariable and nonlinear feedback systems.
  • appreciate the diversity of phenomena in nonlinear systems.

Content

PART 1: MULTIVARIABLE FEEDBACK SYSTEMS (7L + 1 example class, Dr F Forni)

  • Performance measures for multi-input/multi-output systems.
  • Stabilization: stability conditions, all stabilizing controllers, small gain theorem.
  • Models for uncertain systems.
  • Robust stability and performance. Loop shaping design.
  • Design of multivariable systems.

PART 2: NONLINEAR SYSTEMS (7L + 1 example class, Dr I Lestas)

  • Linear and Nonlinear systems; feedback circuits.
  • Differential equations and trajectories.
  • Multiple equilibria, limit cycles, chaos and other phenomena.
  • Examples from biology and mechanics.
  • State space stability analysis:
  • The theorems of Lyapunov, LaSalle invariance principle.
  • Stability of nonlinear circuits and neural behaviors.
  • State-space tools for robustness analysis.
  • Input/output stability analysis:
  • Describing functions
  • Small gain theorems, circle and Popov criteria, passivity.

Further notes

ASSESSMENT

Lecture Syllabus/Written exam  (1.5 hours) - Start of Easter Term/100%

Booklists

Please see the Booklist for Group F Courses for references for this module.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 08/01/2018 14:29

Engineering Tripos Part IIB, 4F2: Robust and Nonlinear Control, 2024-25

Module Leader

Prof F Forni

Lecturer

Prof F Forni

Timing and Structure

Lent term. 14 lectures + 2 computer lab sessions. Assessment: 100% coursework

Prerequisites

3F2 assumed.

Aims

The aims of the course are to:

  • introduce fundamental concepts from nonlinear dynamic systems
  • introduce techniques for the analysis and control of nonlinear and multivariable systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • apply standard analysis and design tools to multivariable and nonlinear feedback systems.
  • appreciate the diversity of phenomena in nonlinear systems.

Content

Part I. ROBUST CONTROL (7L + 1 Computer Lab session, Prof F Forni)

1. Uncertainty and Nonlinearity in control systems: simple models.

2. Signal spaces and system gains.

3. The small-gain theorem and the passivity theorem. Phase versus gain uncertainties

4. Dissipativity theory

5. Robust stability and performance. Stability margins.

6. An introduction to H-infty control. 

7. Gap metrics

PART 2: NONLINEAR SYSTEMS (7L + 1 computer lab session, Prof F Forni)

1. Small and large signal analysis. Contractive systems. Fading memory operators.

2. State-space analysis and Nyquist. Differential stability. Differential dissipativity. Differential circle criterion.

3. Feedback systems: simple models.

4. Phase portrait analysis.

5. Analysis and design of switches and clocks. Robust differential control.

6. Monotone systems. Scale relative graphs (SRGs). Applications in biology.

7. Describing function analysis.

Further notes

ASSESSMENT

Coursework only.

Coursework

Coursework Format

Due date

& marks

[Coursework activity #1  Robust control of haptic interfaces

Coursework 1 brief description

Learning objective:

  • Learn how to model uncertainty in an engineering application
  • Design a robust controller in Matlab

Individual Report 

  anonymously marked

 

28 February 2025

[30/60]

[Coursework activity #2  Feedback oscillations control ]

Coursework 2 brief description

Learning objective:

  • Learn how to model and analyse nonlinear oscillations in feedback systems
  • Design a nonlinear oscillator in a biologically motivated appication

Individual Report

anonymously marked

  28 March 2025

[30/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 19/01/2025 18:26

Engineering Tripos Part IIB, 4F1: Control System Design, 2023-24

Module Leader

Prof M.C. Smith

Lecturer

Prof M Smith

Lab Leader

Prof M Smith

Timing and Structure

Michaelmas term. 12 lectures + 2 examples classes + coursework. Assessment: 75% exam/25% coursework

Prerequisites

3F1 and 3F2 useful

Aims

The aims of the course are to:

  • establish for the students a fundamental approach to the design of linear control systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • understand the role and importance of feedback for the control of uncertain dynamical systems.
  • demonstrate the information conveyed via root locus diagrams for transient behaviour and basic frequency response analysis using Nyquist (polar) and Bode plots.
  • following its basic derivation, illustrate the use of the Nyquist stability criterion with both open loop stable and open loop unstable systems;
  • understand factors which limit achievable performance in feedback systems.
  • use analytical tools to understand trade-offs (e.g. Bode gain/phase relations, sensitivity integrals).
  • translate general requirements for robustness and performance into specifications on the open-loop frequency response.
  • use computer software for simple control system design and system simulation
  • design simple compensators to achieve such specifications.

Content

Control system design (11L)

  • System dynamics, stability and instability, principles and use of root locus plots, derivation of Nyquist stability criterion, Bode theorems and plots.
  • Design of simple P.I.D. controllers and phase compensators. Sensitivity, complementary sensitivity and SISO robustness. Non-minimum phase systems and limitations, bandwidth. Delays in systems.
  • Two degree of freedom design. 

Introduction to Coursework (1L)

Case studies and simulation.

Coursework

Case studies and design by simulation and computer software, e.g. use of Matlab. Four hours DPO time plus report (further four hours).

Coursework Format

Due date

& marks

Coursework activity #1 Final

Coursework 1 brief description

Learning objective:

  • To carry out a controller design using Matlab.
  • The design process to illustrate the design and analysis methods of the course.

Individual Report

anonymously marked

Fri week 9

[15/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 30/05/2023 15:31

Engineering Tripos Part IIB, 4F1: Control System Design, 2025-26

Module Leader

Prof G Vinnicombe

Lecturer

Prof M Smith

Lab Leader

Timing and Structure

Michaelmas term. 12 lectures + 2 examples classes + coursework. Assessment: 75% exam/25% coursework

Prerequisites

3F1 and 3F2 useful

Aims

The aims of the course are to:

  • establish for the students a fundamental approach to the design of linear control systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • understand the role and importance of feedback for the control of uncertain dynamical systems.
  • demonstrate the information conveyed via root locus diagrams for transient behaviour and basic frequency response analysis using Nyquist (polar) and Bode plots.
  • following its basic derivation, illustrate the use of the Nyquist stability criterion with both open loop stable and open loop unstable systems;
  • understand factors which limit achievable performance in feedback systems.
  • use analytical tools to understand trade-offs (e.g. Bode gain/phase relations, sensitivity integrals).
  • translate general requirements for robustness and performance into specifications on the open-loop frequency response.
  • use computer software for simple control system design and system simulation
  • design simple compensators to achieve such specifications.

Content

Control system design (11L)

  • System dynamics, stability and instability, principles and use of root locus plots, derivation of Nyquist stability criterion, Bode theorems and plots.
  • Design of simple P.I.D. controllers and phase compensators. Sensitivity, complementary sensitivity and SISO robustness. Non-minimum phase systems and limitations, bandwidth. Delays in systems.
  • Two degree of freedom design. 

Introduction to Coursework (1L)

Case studies and simulation.

Coursework

Case studies and design by simulation and computer software, e.g. use of Matlab. Four hours DPO time plus report (further four hours).

Coursework Format

Due date

& marks

Coursework activity #1 Final

Coursework 1 brief description

Learning objective:

  • To carry out a controller design using Matlab.
  • The design process to illustrate the design and analysis methods of the course.

Individual Report

anonymously marked

Fri week 9

[15/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 04/06/2025 13:30

Engineering Tripos Part IIB, 4F1: Control System Design, 2021-22

Module Leader

Prof M.C. Smith

Lecturer

Prof M Smith

Lab Leader

Prof M Smith

Timing and Structure

Michaelmas term. 12 lectures + 2 examples classes + coursework. Assessment: 75% exam/25% coursework

Prerequisites

3F1 and 3F2 useful

Aims

The aims of the course are to:

  • establish for the students a fundamental approach to the design of linear control systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • understand the role and importance of feedback for the control of uncertain dynamical systems.
  • demonstrate the information conveyed via root locus diagrams for transient behaviour and basic frequency response analysis using Nyquist (polar) and Bode plots.
  • following its basic derivation, illustrate the use of the Nyquist stability criterion with both open loop stable and open loop unstable systems;
  • understand factors which limit achievable performance in feedback systems.
  • use analytical tools to understand trade-offs (e.g. Bode gain/phase relations, sensitivity integrals).
  • translate general requirements for robustness and performance into specifications on the open-loop frequency response.
  • use computer software for simple control system design and system simulation
  • design simple compensators to achieve such specifications.

Content

Control system design (11L)

  • System dynamics, stability and instability, principles and use of root locus plots, derivation of Nyquist stability criterion, Bode theorems and plots.
  • Design of simple P.I.D. controllers and phase compensators. Sensitivity, complementary sensitivity and SISO robustness. Non-minimum phase systems and limitations, bandwidth. Delays in systems.
  • Two degree of freedom design. 

Introduction to Coursework (1L)

Case studies and simulation.

Coursework

Case studies and design by simulation and computer software, e.g. use of Matlab. Four hours DPO time plus report (further four hours).

Coursework Format

Due date

& marks

Coursework activity #2 Final

Coursework 2 brief description

Learning objective:

  •  
  •  

Individual Report

anonymously marked

Fri week 9

[15/60]

 

Booklists

Please refer to the Booklist for Part IIB Courses for references to this module, this can be found on the associated Moodle course.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 20/05/2021 07:49

Engineering Tripos Part IIB, 4F1: Control System Design, 2018-19

Module Leader

Prof MC Smith

Lecturer

Prof M Smith

Lab Leader

Prof M Smith

Timing and Structure

Michaelmas term. 12 lectures + 2 examples classes + coursework. Assessment: 75% exam/25% coursework

Prerequisites

3F1 and 3F2 useful

Aims

The aims of the course are to:

  • establish for the students a fundamental approach to the design of linear control systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • understand the role and importance of feedback for the control of uncertain dynamical systems.
  • demonstrate the information conveyed via root locus diagrams for transient behaviour and basic frequency response analysis using Nyquist (polar) and Bode plots.
  • following its basic derivation, illustrate the use of the Nyquist stability criterion with both open loop stable and open loop unstable systems;
  • understand factors which limit achievable performance in feedback systems.
  • use analytical tools to understand trade-offs (e.g. Bode gain/phase relations, sensitivity integrals).
  • translate general requirements for robustness and performance into specifications on the open-loop frequency response.
  • use computer software for simple control system design and system simulation
  • design simple compensators to achieve such specifications.

Content

Control system design (11L)

  • System dynamics, stability and instability, principles and use of root locus plots, derivation of Nyquist stability criterion, Bode theorems and plots.
  • Design of simple P.I.D. controllers and phase compensators. Sensitivity, complementary sensitivity and SISO robustness. Non-minimum phase systems and limitations, bandwidth. Delays in systems.
  • Two degree of freedom design. 

Introduction to Coursework (1L)

Case studies and simulation.

Coursework

Case studies and design by simulation and computer software, e.g. use of Matlab. Four hours DPO time plus report (further four hours).

Coursework Format

Due date

& marks

[Coursework activity #1 title / Interim]

Coursework 1 brief description

Learning objective:

  •  
  •  

Individual/group

Report / Presentation

[non] anonymously marked

day during term, ex:

Thu week 3

[xx/60]

[Coursework activity #2 title / Final]

Coursework 2 brief description

Learning objective:

  •  
  •  

Individual Report

anonymously marked

  Wed week 9

[xx/60]

 

Booklists

Please see the Booklist for Group F Courses for references for this module.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 17/05/2018 14:18

Engineering Tripos Part IIB, 4F1: Control System Design, 2017-18

Module Leader

Dr I Lestas

Lecturer

Prof M Smith, Dr I Lestas

Lab Leader

Prof M Smith

Timing and Structure

Michaelmas term. 12 lectures + 2 examples classes + coursework. Assessment: 75% exam/25% coursework

Prerequisites

3F1 and 3F2 useful

Aims

The aims of the course are to:

  • establish for the students a fundamental approach to the design of linear control systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • understand the role and importance of feedback for the control of uncertain dynamical systems.
  • demonstrate the information conveyed via root locus diagrams for transient behaviour and basic frequency response analysis using Nyquist (polar) and Bode plots.
  • following its basic derivation, illustrate the use of the Nyquist stability criterion with both open loop stable and open loop unstable systems;
  • understand factors which limit achievable performance in feedback systems.
  • use analytical tools to understand trade-offs (e.g. Bode gain/phase relations, sensitivity integrals).
  • translate general requirements for robustness and performance into specifications on the open-loop frequency response.
  • use computer software for simple control system design and system simulation
  • design simple compensators to achieve such specifications.

Content

Control system design (11L)

  • System dynamics, stability and instability, principles and use of root locus plots, derivation of Nyquist stability criterion, Bode theorems and plots.
  • Design of simple P.I.D. controllers and phase compensators. Sensitivity, complementary sensitivity and SISO robustness. Non-minimum phase systems and limitations, bandwidth. Delays in systems.
  • Two degree of freedom design. 

Introduction to Coursework (1L)

Case studies and simulation.

Coursework

Case studies and design by simulation and computer software, e.g. use of Matlab. Four hours DPO time plus report (further four hours).

Coursework Format

Due date

& marks

[Coursework activity #1 title / Interim]

Coursework 1 brief description

Learning objective:

  •  
  •  

Individual/group

Report / Presentation

[non] anonymously marked

day during term, ex:

Thu week 3

[xx/60]

[Coursework activity #2 title / Final]

Coursework 2 brief description

Learning objective:

  •  
  •  

Individual Report

anonymously marked

  Wed week 9

[xx/60]

 

Booklists

Please see the Booklist for Group F Courses for references for this module.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 05/10/2017 07:39

Engineering Tripos Part IIB, 4F1: Control System Design, 2019-20

Module Leader

Prof MC Smith

Lecturer

Prof M Smith

Lab Leader

Prof M Smith

Timing and Structure

Michaelmas term. 12 lectures + 2 examples classes + coursework. Assessment: 75% exam/25% coursework

Prerequisites

3F1 and 3F2 useful

Aims

The aims of the course are to:

  • establish for the students a fundamental approach to the design of linear control systems.

Objectives

As specific objectives, by the end of the course students should be able to:

  • understand the role and importance of feedback for the control of uncertain dynamical systems.
  • demonstrate the information conveyed via root locus diagrams for transient behaviour and basic frequency response analysis using Nyquist (polar) and Bode plots.
  • following its basic derivation, illustrate the use of the Nyquist stability criterion with both open loop stable and open loop unstable systems;
  • understand factors which limit achievable performance in feedback systems.
  • use analytical tools to understand trade-offs (e.g. Bode gain/phase relations, sensitivity integrals).
  • translate general requirements for robustness and performance into specifications on the open-loop frequency response.
  • use computer software for simple control system design and system simulation
  • design simple compensators to achieve such specifications.

Content

Control system design (11L)

  • System dynamics, stability and instability, principles and use of root locus plots, derivation of Nyquist stability criterion, Bode theorems and plots.
  • Design of simple P.I.D. controllers and phase compensators. Sensitivity, complementary sensitivity and SISO robustness. Non-minimum phase systems and limitations, bandwidth. Delays in systems.
  • Two degree of freedom design. 

Introduction to Coursework (1L)

Case studies and simulation.

Coursework

Case studies and design by simulation and computer software, e.g. use of Matlab. Four hours DPO time plus report (further four hours).

Coursework Format

Due date

& marks

[Coursework activity #1 title / Interim]

Coursework 1 brief description

Learning objective:

  •  
  •  

Individual/group

Report / Presentation

[non] anonymously marked

day during term, ex:

Thu week 3

[xx/60]

[Coursework activity #2 title / Final]

Coursework 2 brief description

Learning objective:

  •  
  •  

Individual Report

anonymously marked

  Wed week 9

[xx/60]

 

Booklists

Please see the Booklist for Group F Courses for references for this module.

Examination Guidelines

Please refer to Form & conduct of the examinations.

UK-SPEC

This syllabus contributes to the following areas of the UK-SPEC standard:

Toggle display of UK-SPEC areas.

GT1

Develop transferable skills that will be of value in a wide range of situations. These are exemplified by the Qualifications and Curriculum Authority Higher Level Key Skills and include problem solving, communication, and working with others, as well as the effective use of general IT facilities and information retrieval skills. They also include planning self-learning and improving performance, as the foundation for lifelong learning/CPD.

IA1

Apply appropriate quantitative science and engineering tools to the analysis of problems.

IA2

Demonstrate creative and innovative ability in the synthesis of solutions and in formulating designs.

KU1

Demonstrate knowledge and understanding of essential facts, concepts, theories and principles of their engineering discipline, and its underpinning science and mathematics.

KU2

Have an appreciation of the wider multidisciplinary engineering context and its underlying principles.

D1

Wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations.

D4

Ability to generate an innovative design for products, systems, components or processes to fulfil new needs.

E1

Ability to use fundamental knowledge to investigate new and emerging technologies.

E2

Ability to extract data pertinent to an unfamiliar problem, and apply its solution using computer based engineering tools when appropriate.

E3

Ability to apply mathematical and computer based models for solving problems in engineering, and the ability to assess the limitations of particular cases.

E4

Understanding of and ability to apply a systems approach to engineering problems.

P1

A thorough understanding of current practice and its limitations and some appreciation of likely new developments.

P3

Understanding of contexts in which engineering knowledge can be applied (e.g. operations and management, technology, development, etc).

US1

A comprehensive understanding of the scientific principles of own specialisation and related disciplines.

US2

A comprehensive knowledge and understanding of mathematical and computer models relevant to the engineering discipline, and an appreciation of their limitations.

 
Last modified: 28/05/2019 15:07

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