Engineering Tripos Part IIB, 4M3: Spanish, 2019-20
Leader
Lecturer
Timing and Structure
Michaelmas Term. Course given at Intermediate and Advanced Levels; 7 lectures + 7 seminars + coursework Assessment Coursework / 3 Tasks: 2 written reports, 1 oral presentation / End of week 3 (30%), end of week 5 (30%), end of week 8 (40%)
Prerequisites
Spanish at Intermediate Level
Aims
The aims of the course are to:
- To advance understanding in Hispanic science and technology, society and culture.
- To enable all students to consolidate their listening skills and practise their speaking skills in class, while particular emphasis will be put on reading and writing skills outside the class.
Objectives
As specific objectives, by the end of the course students should be able to:
- be confident in speaking/reading/writing whether in a general or work-related situation;
- use the language as a tool to improve understanding of technology, society and culture;
- analyse a topic/an issue in depth, compare all the elements at play, synthesise the major points and make a balanced judgement.
Content
Seminars (7 Lectures, various speakers, subject to changes)
- La historia de la ciencia y la ingeniería en el Mundo Hispano: desde el pasado precolombino hasta el presente.
- Principales avances tecnológicos y su impacto en España.
- La ingeniería y la tecnología en aplicación en la vasta Hispanoamérica.
- La industria tecnológica y sus desafíos en el Mundo Hispano.
- Cómo pueden aplicarse las investigaciones a las necesidades de los países hispanos
- La educación y la ciencia en España.
- Una proyección hacia el futuro
Material to be announced in lectures.
A list of this year's module talks will be available at http://www.eng.cam.ac.uk/teaching/language/module-lectures.htm
Seminars
Associated with each lecture will be a one-hour seminar. This may be held before the lecture for preparation, or following the lecture for discussion purposes.
Coursework
The students will prepare 3 major pieces of coursework:
- Two written reports (30% each)
- Oral presentation (40%)
- The assignments will be marked for both language and content (50% language, 50% content)
|
Coursework |
Format |
Due date & marks |
|---|---|---|
|
Coursework activity #1 Report A structured report of 900 words in the target language. Learning objective:
|
Individual report (900 words) Non-anonymously marked |
End of week 3 [30%] |
|
Coursework activity #2 Report A structured report of 900 words in the target language. Learning objective:
|
Individual report (900 words) Non-anonymously marked |
End of week 5 [30%] |
|
Coursework activity #3 Oral presentation A structured oral presentation (10-15 minutes followed by questions) Learning objective:
|
Individual oral presentation (10-15 minutes followed by questions) Non-anonymously marked |
Last session (week 8) [40%] |
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.
P4
Understanding use of technical literature and other information sources.
Last modified: 31/05/2019 12:15
Engineering Tripos Part IIA, 3F2: Systems & Control, 2022-23
Module Leader
Lecturer
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 27/01/2023 07:18
Engineering Tripos Part IIA, 3F2: Systems & Control, 2024-25
Module Leader
Lecturer
Prof R Sephulchre
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 28/10/2024 07:49
Engineering Tripos Part IIA, 3F2: Systems & Control, 2017-18
Module Leader
Lecturer
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Ball and beam experiment (state trajectories, nonlinear control). Laboratory report only.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please see the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 12/02/2018 15:02
Engineering Tripos Part IIA, 3F2: Systems & Control, 2023-24
Module Leader
Lecturer
Prof G Vinnicombe, Prof R Sephulchre
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 30/05/2023 15:21
Engineering Tripos Part IIA, 3F2: Systems & Control, 2019-20
Module Leader
Lecturer
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please see the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 05/08/2020 08:31
Engineering Tripos Part IIA, 3F2: Systems & Control, 2025-26
Module Leader
Lecturer
Prof R Sephulchre
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 04/06/2025 13:21
Engineering Tripos Part IIA, 3F2: Systems & Control, 2021-22
Module Leader
Lecturer
Lecturer
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 20/05/2021 07:39
Engineering Tripos Part IIA, 3F2: Systems & Control, 2020-21
Module Leader
Lecturer
Lecturer
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please refer to the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 28/08/2020 11:06
Engineering Tripos Part IIA, 3F2: Systems & Control, 2018-19
Module Leader
Lecturer
Lab Leader
Timing and Structure
16 Lectures, Lent Term
Aims
The aims of the course are to:
- make students familiar with “state-space” methods of modelling and analysing dynamic systems. These methods are extremely important for control engineering, signal processing, and related subjects.
Objectives
As specific objectives, by the end of the course students should be able to:
- understand what a state-space model is, and how to obtain such a model;
- relate state-space models to transfer-function models;
- analyse the behaviour and structure of a state-space model;
- have some understanding of feedback design using state-space, transfer function and root-locus techniques, and be able to relate them to each other;
- appreciate the need for and usefulness of state observers, and their role in feedback and other systems.
Content
State-space models (6L)
- Review of second-year material (linear algebra, transfer functions, poles)
- Formulation from physical models
- Linearising nonlinear models
- Relationship to transfer function matrix (multiple inputs/outputs)
- Free and forced responses (state-transition matrix convolution, stability)
- Interconnections of systems
Feedback system design (4L)
- Review of second-year material (feequency responses, controller structures, objectives of feedback design).
- The root-locus diagram
- Routh-Hurwitz criterion (examples of use).
State estimation (3L)
- Observability.
- State observer; Oberver design.
- Connections to Kalman filters, sensor fusion etc.
Control in state-space framework (3L)
- Controllability.
- State feedback and pole-placement.
- Optimal control.
- State observer combined with state feedback
Examples papers
Paper 1: State-space models - issued in week 3
Paper 2: Root locus - issued in week 5
Paper 3: Observers and state feedback - issued in week 7
Coursework
Inverted pendulum experiment (state feedback). Laboratory report and/or full technical report.
Ball and beam experiment (state trajectories, nonlinear control). Laboratory report only.
Learning objectives:
- State feedback
- Pole placement
- Control design
Practical information:
- Sessions will take place in EIETL laboratory, on Wednesdays and Fridays of full term
- Students will find it helpful to read through the lab sheet in advance of carrying out the experiment.).
Full Technical Report:
Students will have the option to submit a Full Technical Report.
Booklists
Please see the Booklist for Part IIA 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.
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.
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.
US3
An understanding of concepts from a range of areas including some outside engineering, and the ability to apply them effectively in engineering projects.
Last modified: 05/08/2020 08:32
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