MECH ENG 7080 - Modern Control Systems
North Terrace Campus - Semester 1 - 2022
General Course Information
Course Code MECH ENG 7080 Course Modern Control Systems Coordinating Unit School of Mechanical Engineering Term Semester 1 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Available for Study Abroad and Exchange Incompatible MECH ENG 7047, MECH ENG 7034 Assumed Knowledge MECH ENG 7111 Course Description This hands-on course addresses how to control complex dynamic systems using modern state-space techniques. This involves time domain descriptions of dynamic systems using state-space system models. The characteristics responsible for the dynamic response (poles, zeros, eigenvalues) are presented. Control laws using state-space methods are introduced, including specification of controller characteristics, pole placement, and optimal (LQR) control. State observers are presented, including observer design using both pole placement and optimal (Kalman) observers. The implementation of state space controllers and Kalman filters in digital systems is also covered. The learning objectives of the course are achieved using various assessments, including weekly laboratories in which students design control systems for a series of experimental apparatus.
Course Coordinator: Rini Akmeliawati
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn succesful completion of this course, students will be able to:
- Construct state space models of dynamic systems.
- Explain basic control concepts such as controllability, observability, poles and zeros, stability
- Design full-state control systems
- Design optimal control systems
- Design and build a state estimator
- Design digital controllers
- Simulate state space systems in MATLAB/Simulink
- Have had experience with designing real control systems
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)
Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
Required ResourcesCourse Notes available on MyUni.
- Dorf and Bishop “Modern Control Systems”
- Franklin, Powell and Emami-Naeini “Feedback Control of Dynamic Systems”
- Nise “Control Systems Engineering”
- Emmanuel C. Ifeachor, Barrie W. Jervis, "Digital Signal Processing – A Practical Approach"
- B. P. Lathi, "Linear Systems and Signals," Oxford University Press.
- Franklin G. F., Powell J. D., Workman M., "Digital Control of Dynamic Systems"
Online LearningSignificant links available to online resources available on MyUni.
Learning & Teaching Activities
Learning & Teaching ModesOnline lectures supported by computer lab-based tutorials and laboratory experiments.
All lectures will be delivered online. These online lectures will be complemented by learning activities including computer lab-based tutorials, quizzes, assignments and a face-to-face laboratory experiment. Lecturers will also be available weekly at designated times for consulting in person or via Zoom. There will also be the option to participate in all activities entirely remotely.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.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 examination
Learning Activities SummaryIntroduction to State Space Modelling (1 lecture)
Lagrangian Mechanics (1 lecture)
Linearisation of Non-linear Differential Equation (1 lecture)
Construction of State Space Models (1 lecture)
Modelling Multiple DOF Systems (1 lecture)
Conversion between SS to TF and back again: Control canonical, observer canonical, Jordan form (1 lecture)
Solution to state equations, poles, zeros and stability (1 lecture)
Controllability and Observability (1 lecture)
Feedback Control & Pole Placement (1 lecture)
Observers (Estimators) (1 lecture)
Optimal Control (LQR) (1 lecture) (1 lecture)
Optimal Observers (Kalman-Bucy Filters, LQG) (1 lecture)
Reduced Order Observers (1 lecture)
Compensators (1 lecture)
Reference Input & Command Tracking (1 lecture)
Digital Control: Sampling & Quantization (1 lecture)
Digital Control Design by Emulation (1 lecture)
Summary (1 lecture)
Computer lab-based tutorials using MATLAB/SIMULINK and Quanser QuaRC (12 tutorials)
Specific Course RequirementsNil
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 SummaryAssignments : 2 x 10%
Webinar Quizzes: 8%
Lab Quizzes: 7%
Mini Project: 15%
** See Assessment Related Requirements.
This assessment breakdown complies with the University's Assessment for Coursework Programs Policy.
The Modern Control Systems coursework comprises computer-lab based tutorials, quizzes, a mini project and assignments. The computer lab-based tutorials are designed to provide instruction of Matlab and Simulink while simultaneously developing the understanding of the students’ control knowledge through simulation.
Assessment Related RequirementsNote that the laboratory experiment is compulsory.
Assessment DetailThe assessment comprises 16 webinar quizzes each worth 0.5 mark (8% in total), 12 CARM Lab quizzes each worth 1 mark (12% in total), one Mini Project (10%), and two assignments submitted electronically worth 20%. The exam comprises 50% of the overall mark.
SubmissionAll quizzes, assignments and practical reports must be submitted electronically via MyUni as per instructions for each assessment. Late reports will be penalised 10% per day. All quizzes, tutorials and assignments are submitted online using Mobius/MyUni. Late submissions are not possible as Mobius/MyUni automatically prevents submission after the due time on the due date, unless an extension has been granted and implemented in Mobius/MyUni by the Course Coordinator.
Extensions for assignments will only be given in exceptional circumstances and a case for this with supporting documentation can
be made in writing via email to the Course Coordinator. The Course Coordinator must receive a completed Application for Assessment Extension form (https://www.adelaide.edu.au/policies/3303/?dsn=policy.document;field=data;id=7446;m=view) prior to the Assessment Deadline when a student is seeking an extension. There are only three grounds for which an extension can be granted: Medical Circumstances, Compassionate Circumstances and/or Extenuating Circumstances. Course Coordinators cannot grant extensions based on balancing student workloads.
There will be no opportunities for re-submission of work of unacceptable standard.
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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