MECH ENG 4102 - Advanced PID Control
North Terrace Campus - Semester 1 - 2020
General Course Information
Course Code MECH ENG 4102 Course Advanced PID Control Coordinating Unit School of Mechanical Engineering Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 5 hours per week Available for Study Abroad and Exchange Y Assumed Knowledge MECH ENG 1007, MECH ENG 2019 & MECH ENG 3028 Course Description Advanced topics in automatic control system design with a focus on PID Control. Major topics include: system identification for low-order systems, frequency domain analysis of stability and sensitivity, and PID tuning laws and their derivation. Techniques used to analyse and accommodate uncertainty and disturbances in practical systems. The contact time involves: one weekly lecture, regular online assignments, and one mandatory weekly laboratory practical with associated workbook and lab report assessments. Matlab/Simulink is the programming environment used to design and analyse the control systems both theoretically and using hands-on control system apparatus in the lab.
Course Coordinator: Dr William Robertson
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course students will be able to:
1 Explain and generalise key concepts in the field of automatic control; 2 Design a plant using both time domain and frequency methods, both theoretically and on
real plant equipment;
3 Design a given plant, both without and with a control system, disturbances, and
4 Design and tune a PID controller using standard approaches; 5 Assess and modify a generalised control system for performance, stability, and
6 Apply signal processing and control system design in hardware for controlling real
The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
The course is designed to develop the following Elements of Competency: 1.1 1.2 1.3 1.4 1.5 1.6 2.1 2.2 2.3 2.4 3.1 3.2 3.3 3.4 3.5 3.6
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1-6 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1-6 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
1-6 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
1-6 Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
1, 2, 6
Course Notes available from the Image & Copy Centre or softcopy on MyUni.
Dorf and Bishop, Modern Control Systems, Chapters 5, 6, 7, 8, 9, 10, 12; Astrom and Hagglund, PID Controllers: Theory, Design and Tuning, Chapters 4 & 5
Maciejowski, Multivariable Feedback Design, Chapter 1; Xue, Chen and Atherton, Linear Feedback Control – Analysis and Design with Matlab, Chapter 6; Yu, Autotuning of PID Controllers, Chapters 2 and 3; Younkin, Industrial Servo Control Systems – Fundamentals and Applications.
Significant links available to online resources available on MyUni.
Learning & Teaching Activities
Learning & Teaching Modes
54 hours lectures supported by computer-based tutorials and a problem-based practical laboratory.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
As per university recommendations, it is expected that students spend 48hrs/week during teaching periods, and that a 3 unit course has a minimum workload of 156 hours regardless of the length of the course. Additional time may need to be spent acquiring assumed knowledge, working on assessment during non-teaching periods, and preparing for and attending examinations.
Learning Activities Summary
Below is a breakdown of the scheduled learning activities for this course:
Topic 1: Process Models (5%)
- Algebraic Systems
- Static models
- Dynamic models
- First Order Time Delay
- First order
- First Order Time Delay
- Second order
- Second Order Time Delay
- Time domain
- Frequency domain
Topic 2: Frequency Domain (5%)
- Plotting frequency response function
- Bode Plots : Magnitude & Phase vs Frequency
- Nyquist - Complex Plane for G(jω)H(jω)
- Nichols Charts - Magnitude versus Phase Angle
- Frequency response of second order systems
Topic 3: Frequency Domain & Stability (5%)
- Review of Stability
- Root-Locus: s-plane
- The Cauchy Criterion
- The Nyquist Stability Criterion
- Gain, Phase & Delay Margins
- Effect of time delays on stability
Topic 4: Relationship between Open and Closed-Loop Frequency Response (5%)
- The basic relationship between open and closed-loop responses
- M and N Circles
- Maximum amplitude of closed-loop response
- Frequency at which this occurs (resonance frequency)
Topic 5: PID Control (5%)
- Various forms of Proportional-Integral-Derivative (PID) controllers
- The role of each elemental controller
- Actuator saturation and integral windup
- Proportional and derivative kick
Topic 6: PID Tuning - An Introduction (5%)
- Frequency domain modeling of simple process dynamics
- Ultimate gain
- Feature-based PID tuning techniques
- Chien, Hrones and Reswick
Topic 7: Advanced PID Tuning (5%)
- Pole Placement
- Dominant Poles
- Pole-Zero Cancellation
Topic 8: Sensitivity Relationships and Controller Design (5%)
- The sensitivity function
- The complementary sensitivity function
- The sensitivity of open loop and closed loop
- Loop shaping
Topic 9: More On Sensitivity Relationships and Robust Control (5%)
- Bode’s gain-phase relationship and integral theorem
- Relationship between sensitivity and proximity of frequency response function to critical point
- Relationship between sensitivity and phase and gain margins
- Robust stability criterion
Topic 10: New Tuning Methods - KT Tuning (5%)
- The issues with ZN tuning
- The need for alternative tuning methods
- Tuning to achieve a desired sensitivity
- Kappa-Tau tuning method
Topic 11: ITAE Optimal Systems (5%)
- Various time domain performance metrics
- integral of the square of the error
- integral of the absolute error
- integral of the time multiplied by the absolute error
- integral of the time multiplied by the square of the error
- Controller design using ITAE
Topic 12: Internal Model Control (5%)
- Internal Model Control (IMC)
- Advantages and disadvantages of model-based controllers
- Factorisation into invertible and non-invertible components
- The necessity for controllers to be proper
Topic 13: Servo Control (5%)
- Mechanical servo systems, including motors and amplifiers,
- transmission elements
- Backlash, its effect and techniques for reducing its influence
- Feedforward elements
- Dual loop control
Topic 14: Automatic Tuning (5%)
- The theory behind auto-tuning algorithms
- How to use auto-tuning algorithms
- The “relay method”
Matlab / Simulink modeling (30%)
- Design of a control system for a real physical system
- Hands-on implementation using Simulink and Space Control Desk
Text book: Nil
Specific Course Requirements
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Task Weighting (%) Individual/ Group Formative/ Summative Due (week)* Hurdle criteria Learning outcomes Lecture quizzes 5 Individual Summative Weeks 1-12 1. 2. 3. 4. 5. Assignments 20 Individual Summative Weeks 3, 6, 9, 12 1. 2. 3. 4. 5. Lab workbooks 10 Group Summative Week 2, 4, 6, 8 1. 2. 4. 6. Lab project report 15 Group Summative Week 13 1. 2. 4. 5. 6. Exam 50 Individual Summative Exam period 1. 2. 4. 5. Total 100
This assessment breakdown is registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s): 1. a. i 1. a. ii 1. b. 3.
All lectures and assessments are all intended to reinforce the learning outcomes of this course.
The assignments and lab sessions are designed to provide instruction of Matlab and Simulink while simultaneously developing the understanding of the students’ control knowledge through simulation.
The problem-based laboratory classes are intended to provide students with some practical experience in developing controllers for real (non-ideal) plants, as well as the use of instrumentation, and experience in report writing and communicating their results.
The examination is a summative assessment and is intended to assess the student’s knowledge and understanding of the course material and how it fits into the global engineering context.
Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.
As all invigilated exams have now been cancelled, we will shift to a TAKE HOME exam as the final assessment for the course. This will be run through MyUni and Mobius and will require all students to access the exam script within a short time window, complete questions under exam conditions in their home, and submit answers electronically. It is likely that there will be some Matlab questions and some hand-written questions which are photographed and uploaded.
To accommodate the quirks of a take-home exam, the assessment structure of course course has changed. The exam is now worth 55% of the course with other assessments increased to compensate.
Assessment Related RequirementsNil.
No information currently available.
All assignments and lab reports will be submitted electronically via MyUni.
Late assignments and reports will be penalised 10% per day. Extensions for assignments will only be given in exceptional circumstances and a case for this with supporting documentation can be made in writing after a lecture or via email to the lecturer. Hard copy assignments will be assessed and returned in 2 weeks of the due date. There will be no opportunities for re-submission of work of unacceptable standard. Due to the large size of the class feedback on assignments will be limited to in-class discussion resulting from questions from students.
All tutorials are submitted online using MyUni. Late tutorials cannot be accepted as they are submitted electronically via MyUni which automatically prevents late submission.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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