ENME403-25S1 (C) Semester One 2025

Linear Systems Control and System Identification

15 points

Details:
Start Date: Monday, 17 February 2025
End Date: Sunday, 22 June 2025
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 2 March 2025
  • Without academic penalty (including no fee refund): Sunday, 11 May 2025

Description

State-space modelling, solution and analysis of state-space equations. Control systems aspects include state feedback and pole placement, state estimation and optimal control. System identification, which is complementarily related to control systems design/analysis will develop and solve linear methods of model identification and creation from data.

Modern linear systems theory is the backbone of a range of advanced dynamic systems modelling and analyses with direct industry relevance across a range of fields, including aerospace, automotive, automation and others. This course covers both control and system identification methods, which are relevant to these industries and engineering practice.

Additional Prerequisites Note:
ENME403 is available to any Fourth-Year Engineering student who has completed either ENME303 or ENEL321 and has also completed their Second-Year Engineering requirements.
All non-Mechanical Students:
Please contact your Departmental Fourth-Year Director of Studies to request enrolment into this course.

Learning Outcomes

  • Washington Accord (V4) Summary of Graduate Attributes attained in this course:
     WA2 – Problem Analysis
     WA3 – Design/Development of Solutions
     WA4 – Investigation
     WA5 – Tool Usage
     WA6 – The Engineer and the World
     WA8 – Individual and Collaborative Teamwork
     WA9 – Communication
     WA11 – Lifelong Learning

  • Course topics with Learning Outcomes (and Washington Accord (WA) and UC Graduate Attributes) identified.

    1. Modern Control and Linear Systems: Introduction to state space systems and mathematics; State space description of dynamic systems: CTS and DTS; State space analysis, Stabilizable: Observability and Controllability, Stability; State space control design; Modern optimal control methods and stability analysis
             1.1. Understand system theory topics: including state space modelling of SISO and MIMO systems, natural and forced responses, state transition matrix, stability, controllability and observability (WA2, WA4)
             1.2. Ability to derive, interpret and solve problems using modern state space control methods for continuous time systems (CTS) and discrete time systems (DTS), and simulate these feedback control systems (WA2, WA5)
             1.3. Understand system stability, controllability, observability, and stabilizability in modern control, and able to use these tools in systems analysis and design (WA2, WA3, WA4, WA5) (EIE4)
             1.4. Ability to apply and solve problems for the design of modern state space and optimal control problems, including application to complex, multi-input, multi-output (MIMO) systems (WA2, WA3) (EIE3)
    2. System Identification (ID): Introduction to System ID and identifiability; Integral-based Methods; Gradient descent and Regression based methods
             2.1. Understand modern system identification methods using time domain and state space models (WA2)
             2.2. Ability to derive and solve system identification problems using modern state space system models and experimental data, including integral-based methods and least-squares based methods (WA2, WA4, WA5) (EIE4)
             2.3. Understand system ID methods and their implementation and application via project-based learning (WA2, WA3, WA10) (EIE2)
    3. Overarching course objectives, as per ENME303 and including:
             3.1. Able to apply modern modelling and control or system identification methods and analysis to a wider spectrum of real-life engineering problems via laboratories, problems, case studies and projects (WA6, WA9, WA10) (EIE1, EIE2, EIE5)
             3.2. Lay a theoretical and mathematical foundation for the analysis of advanced control systems (WA5, WA6, WA12) (EIE1, EIE3, EIE4, EIE5)
    • University Graduate Attributes

      This course will provide students with an opportunity to develop the Graduate Attributes specified below:

      Employable, innovative and enterprising

      Students will develop key skills and attributes sought by employers that can be used in a range of applications.

Prerequisites

Restrictions

ENEL430 and ENME603

Timetable 2025

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 09:00 - 11:00 E8 Lecture Theatre
17 Feb - 6 Apr
28 Apr - 1 Jun
Lecture B
Activity Day Time Location Weeks
01 Wednesday 10:00 - 12:00 E8 Lecture Theatre
17 Feb - 6 Apr
28 Apr - 1 Jun
Computer Lab A
Activity Day Time Location Weeks
01 Thursday 12:00 - 15:00 Civil - Mech E201 Mech Computer Lab
19 May - 1 Jun
02 Thursday 15:00 - 18:00 Civil - Mech E201 Mech Computer Lab
19 May - 1 Jun
Drop in Class A
Activity Day Time Location Weeks
01 Tuesday 15:00 - 16:00 Ernest Rutherford 140
17 Feb - 6 Apr
28 Apr - 1 Jun
02 Tuesday 16:00 - 17:00 Ernest Rutherford 140
17 Feb - 6 Apr
28 Apr - 1 Jun
03 Tuesday 17:00 - 18:00 Ernest Rutherford 140
17 Feb - 6 Apr
28 Apr - 1 Jun

Course Coordinator

Geoff Chase

Lecturer

Geoff Chase

Notes

For detailed course, policy, regulatory and integrity information, please refer to the UC web site, or see relevant Course or Department LEARN pages, (which are available to enrolled students).

Indicative Fees

Domestic fee $1,268.00

International fee $6,238.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mechanical Engineering .

All ENME403 Occurrences

  • ENME403-25S1 (C) Semester One 2025
  • ENME403-24SU2 (D) Summer Nov 2024 start (Distance)