Module Details
| Module Code: |
INTR7033 |
| Title: |
Modelling and Control
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Long Title:
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Modelling and Control
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| NFQ Level: |
Intermediate |
| Valid From: |
Semester 1 - 2020/21 ( September 2020 ) |
| Field of Study: |
5213 - Interdisciplinary Engineering
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| Module Description: |
This module serves as an introduction to linear time-invariant control systems. The aim of this module is to equip students with the capability to design and analyse industrial control systems. An active learning approach is adopted where a typical lecture will commence with a short overview of the theory, after which students are encouraged to investigate concepts like feedback, on-off control, proportional control, proportional plus integral control through simulation and application to laboratory-scale equipment
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| Learning Outcomes |
| On successful completion of this module the learner will be able to: |
| # |
Learning Outcome Description |
| LO1 |
Describe the dynamics of commonly encountered systems using first-order transfer functions, with or without time-delay. |
| LO2 |
Construct and validate a system model, which reflect the main system dynamics and create a Laplace Transfer Function for the process. |
| LO3 |
Analyse single input single output linear time-invariant control loops for performance and stability. |
| LO4 |
Design and implement a controller, based on a linear single-input, single-output model for a selected application by working effectively as part of a team. |
| LO5 |
Use computer-aided design tools to identify, model, analyse, and design feedback controllers and use ICT tools to communicate effectively the analysis of the modelling and control concepts. |
| LO6 |
Discuss, through the use of relevant examples and case-studies, the impact of control systems on people and the environment |
| Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
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Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
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| No incompatible modules listed |
Co-requisite Modules
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| No Co-requisite modules listed |
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
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| No requirements listed |
| Indicative Content |
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Theory
Develop different types of models like flow balance models and transfer function models. Learn feedback principles, block diagram algebra, first order dynamic behavior.
Learn to design/tune different closed loop control strategies like proportional (P), proportional + integral (PI) and Proportional + Integral + Derivative (PID) control. Tuning rules like Ziegler Nichols and Cohen Coon will be investigated. Establish stability criteria, time domain performance metrics like overshoot, settling time and steady state error.
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Simulation
Curve fitting and plotting data in MS Excel, define transfer functions in MATLAB and Simulink, saving/loading files, copying plots to MS Word, calculating closed-loop transfer functions, determine poles and zeros, obtain and analyse time-domain responses, perform a basic closed-loop performance evaluation, create closed-loop systems in Simulink, introduce simple non-linearities, transfer results between Simulink and MATLAB.
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Project
Learn to use specific equipment and adhere to safety regulations, adopt and practice 'best practice' with regard to experimental procedures, practice documenting experimental results, learn to use data acquisition hardware and software, perform system identification experiment and obtain an open-loop response, determine appropriate model, assess adequacy of the model, design and implement proportional controller, design and implement PI controller, evaluate real-time performance as compared with results from simulation and account for discrepancies, document results.
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Graduate Attributes
Writing skills will focus on learning to write using a formal report structure, including research methods, referencing, writing an abstract, creating professional diagrams. Teamwork will focus on communication within groups, documenting and sharing project work and evaluating team performance. Ethical considerations of control systems by examining case studies demonstrating benefits of control systems to humankind.
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Module Content & Assessment
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| Assessment Breakdown | % |
|---|
| Coursework | 100.00% |
Assessments
| No End of Module Formal Examination |
| Reassessment Requirement |
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
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The University reserves the right to alter the nature and timings of assessment
Module Workload
| Workload: Full Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lecture |
Contact |
Short lecture followed by active learning in which students explore learning topic through simulation and experimentation |
Every Week |
2.00 |
2 |
| Lab |
Contact |
Students work in groups on practical application to model and control a specified system. Software like MS Excel, MATLAB/Simulink will be used to interact with the lab process. |
Every Week |
2.00 |
2 |
| Independent & Directed Learning (Non-contact) |
Non Contact |
Revision of lecture notes, preparation for assessment |
Every Week |
3.00 |
3 |
| Total Hours |
7.00 |
| Total Weekly Learner Workload |
7.00 |
| Total Weekly Contact Hours |
4.00 |
| Workload: Part Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lecture |
Contact |
~1/2 hour lecture followed by active learning in which students explore learning topic through simulation |
Every Week |
1.00 |
1 |
| Lab |
Contact |
Students work in groups on practical application to model and control a specified system. Software like MS Excel, MATLAB/Simulink will be used to interact with the lab process. |
Every Week |
2.00 |
2 |
| Independent & Directed Learning (Non-contact) |
Non Contact |
Revision of lecture notes, preparation for assessment |
Every Week |
4.00 |
4 |
| Total Hours |
7.00 |
| Total Weekly Learner Workload |
7.00 |
| Total Weekly Contact Hours |
3.00 |
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Module Resources
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| Recommended Book Resources |
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Karl Johan Åström, Richard M. Murray. (2016), Feedback Systems: An Introduction for Scientists and Engineers, 2nd. 1-6,9,11, Princeton University Press Available at http://www.cds.caltech.edu/~murray/amwiki/index.php/Second_Edition, [ISBN: 9780691135762].
| | Supplementary Book Resources |
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G.F. Franklin, J.D. Powell and A. Emami-Naeini. (2019), Feedback Control of Dynamics Systems, 8th Edition. Pearson, p.928, [ISBN: 9781292274522].
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Richard C. Dorf, Robert H. Bishop. (2017), Modern control systems, 13th edition. Pearson, p.1032, [ISBN: 9781292152974].
| | This module does not have any article/paper resources |
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| Other Resources |
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website, Control Tutorials for Matlab and
Simulink, Carnegie Mellon University,
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website, Dr. T. Edgar. University of Texas, Austin, Tx.,
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