MECH ENG 7034 - Advanced Digital Control
North Terrace Campus - Semester 2 - 2021
-
General Course Information
Course Details
Course Code MECH ENG 7034 Course Advanced Digital Control Coordinating Unit School of Mechanical Engineering Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange N Incompatible MECH ENG 4053, MECH ENG 4123 Assumed Knowledge Continuous Time Dynamics and Control e.g. MECH ENG 3028 Assessment Assignments, final exam Course Staff
Course Coordinator: Mr James O'Connell
Course Timetable
The full timetable of all activities for this course can be accessed from .
-
Learning Outcomes
Course Learning Outcomes
On successful completion of this course students will be able to:
1 Apply discrete state-space design techniques; 2 Analyse discrete plant models and design digital controllers able to meet defined specifications; 3 Create digital filters to meet defined specifications; 4 Apply fuzzy logic to the design of control systems; 5 Recognise the responsibility of engineers to the community for the safety issues associated with the use of control systems; and 6 Recognise the need to undertake lifelong learning.
The above course learning outcomes are aligned with the Engineers Australia .
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, 3, 4 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
2-4 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
2-4 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
5 Intercultural and ethical competency
- adept at operating in other cultures
- comfortable with different nationalities and social contexts
- able to determine and contribute to desirable social outcomes
- demonstrated by study abroad or with an understanding of indigenous knowledges
5 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
2-4, 6 -
Learning Resources
Required Resources
Lecture Notes provided
Recommended Resources
Emmanuel C. Ifeachor, Barrie W. Jervis, Digital Signal Processing – A Practical Approach, 2nd Edition, Prentice Hall, 2002, ISBN 0201-59619-9
B. P. Lathi, Linear Systems and Signals, Oxford University Press (2nd ed.), July 2004,
ISBN-0-195-15833-4
Franklin G. F., Powell J. D., Workman M., Digital Control of Dynamic Systems, 3rd ed., Prentice Hall, 1997, ISBN 0201820544
Stuart J. Russell, Peter Norvig, Artificial Intelligence: A Modern Approach, 2nd Edition,
Prentice Hall, 2002, ISBN 0137903952
Online Learning
K. Passino, S. Yurkovich, Fuzzy Control, , [accessed: May 2006]
MyUni
-
Learning & Teaching Activities
Learning & Teaching Modes
The course takes a flexible approach to teaching and learning with material delivered, concepts explored and skills developed using a range of techniques. A flipped model is utilised with interactive sessions used for presentation of material, exploration of concepts and discussion of directed reading. A series of diagnostic quizzes is used to establish existing knowledge and the assimilation of taught concepts.
Laboratories are centred upon project based learning with case studies used to provide hands-on experience.
Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Indicative workload is 13 hours per week
Activity Hours Interactive lecture sessions 12 Online activities 24 Laboratories (optional) 6 Self study 56 Directed reading 12 Assignments 45 Learning Activities Summary
Digital signal processing (DSP) [4 weeks]- z-Transform and its application
- Fast Fourier Transform and signal spectra
- Aliasing, over-sampling and decimation
- Signal-to-Noise ratio (SNR)
- Fixed-point and floating point arithmetic
- Digital filters: FIR/IIR filter design
- Micro-controller & DSP based implementation of FIR and IIR filters
- FPGA based FIR filter implementation (distributed arithmetic)
- Adaptive filters
- Design by emulation of continuous-time systems
- Discretization of continuous-time systems (ZOH, Tustin, forward rectangular)
- Discrete state-space models
- Canonical forms (controller, observer, modal, Jordan)
- Direct digital control design
- Prediction estimators (full order, reduced order)
- Current estimators (full order, reduced order)
- Tracking systems
- System Identification
- Overview of Artificial Intelligence in robotics and mechatronics applications
- Introduction to fuzzy logic, fuzzy statements, fuzzy sets, and fuzzy control
- Fuzzification, fuzzy-inference and defuzzification
- Fuzzy logic simulation packages
- Fuzzy logic control applications
- Fuzzy identification and estimation
- Artificial Neural Networks
- Neuro-Fuzzy technology
Specific Course Requirements
N/A
-
Assessment
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 Summary
* The specific due date for each assessment task will be available on MyUni.Assessment Task Weighting (%) Individual/ Group Formative/ Summative Due (week)* Hurdle criteria Learning outcomes Quizzes & exercises 25 Individual Summative Weeks 1-12 1. 2. 3. 4. Assignments 30 Individual Summative Weeks 1-12 1. 3. 4. Online Examinations 45 Individual Summative Weeks 4-12 1. 2. 3. 4. Total 100
This assessment breakdown complies with the University's Assessment for Coursework Programs Policy.Assessment Related Requirements
N/A
Assessment Detail
Assignments 30%
Requires the design, implementation and test of digital filters & controllers. Submission of an engineering report and developed software.
Quizzes & exercises 25%
Online Examinations 45%Submission
Fully commented source code and associated assignment documentation must be submitted through MyUni. Late submissions are subject to a penalty of 10% per day. Re-submissions are not allowed except under extenuating circumstances. Assignments will normally be returned within 2 working weeks.
Course Grading
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 .
-
Student Feedback
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.
-
Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
-
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
-
Fraud Awareness
Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.
The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.
