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MECH ENG 4080 - Modern Control Systems

North Terrace Campus - Semester 1 - 2025

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.

  • General Course Information
    Course Details
    Course Code MECH ENG 4080
    Course Modern Control Systems
    Coordinating Unit Mechanical Engineering
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hours per week
    Available for Study Abroad and Exchange
    Incompatible MECH ENG 3028, MECH ENG 4123
    Assumed Knowledge MECH ENG 2019, MECH ENG 3111
    Assessment Quizzes, assessments, reports, exam
    Course Staff

    Course Coordinator: Rini Akmeliawati

    Associate Professor Rini Akmeliawati
    Course Timetable

    The full timetable of all activities for this course can be accessed from .

  • Learning Outcomes
    Course Learning Outcomes
    On succesful completion of this course, students will be able to:
    1 Construct state space models of dynamic systems.
    2 Explain basic control concepts such as controllability, observability, poles and zeros, stability
    3 Design full-state control systems
    4 Design optimal control systems
    5 Design and build a state estimator
    6 Design digital controllers
    7 Simulate state space systems in MATLAB/Simulink
    8 Have had experience with designing real control systems

     
    The above course learning outcomes are aligned with the Engineers 最新糖心Vlog . The course develops the following EA Elements of Competency to levels of introductory (A), intermediate (B), advanced (C):  
     
    1.11.21.31.41.51.62.12.22.32.43.13.23.33.43.53.6
    B B C C C B C C C B B B B C B A
    最新糖心Vlog Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    最新糖心Vlog 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.

    1-8

    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.

    1-8
  • Learning Resources
    Required Resources
    Course Notes available on MyUni.
    Recommended Resources
    • 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 最新糖心Vlog Press.
    • Franklin G. F., Powell J. D., Workman M., "Digital Control of Dynamic Systems"
    Online Learning
    Significant links available to online resources available on MyUni.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    Online 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. 
    Workload

    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 48 hours/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 assessments during non-teaching periods, and preparing for and attending the final examination.
    Learning Activities Summary

    Introduction 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 Requirements
    Nil
  • Assessment

    The 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Task Type Due (week)* Weighting Learning Outcome
    Assignments x 2 Formative & Summative TBD 20%
    Webinar Quizzes Summative TBD 8%
    Lab Quizzes Summative TBD 8%
    Mini Project Formative & Summative TBD 14%
    Exam / Test Summative Exam period 50%

    ** See Assessment Related Requirements.

    This assessment breakdown complies with the 最新糖心Vlog's Assessment for Coursework Programs Policy.


    The coursework comprises weekly workshops, online webinars, computer-lab-based experiments, quizzes, a mini project, and assignments. The computer lab-based experiments are designed to provide instruction in MATLAB and Simulink while simultaneously developing the understanding of the students’ control knowledge through simulation.
    Assessment Related Requirements
    Note that the laboratory experiment is compulsory.
    Assessment Detail
    The assessment comprises 16 webinar quizzes each worth 0.5 mark (8% in total), 16 CARM Lab quizzes each worth 0.5 mark (8% in total), one Mini Project (14%), and two assignments submitted electronically worth 20%. The exam comprises 50% of the overall mark.
    Submission
    All 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 (/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.

    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 .

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    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 最新糖心Vlog 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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