Course handbook
Description
This course is intended to introduce students to a range of techniques for control and estimation for nonlinear systems. Specifically, the course will cover some basic concepts of nonlinear systems and control theory; nonlinear model predictive control; and modern estimation and observer techniques for nonlinear systems. The course includes laboratory and simulation experiments to apply the concepts taught.
Availability2021 Course Timetables
Callaghan
- Semester 2 - 2021
Learning outcomes
On successful completion of the course students will be able to:
1. Design and implement simple feedback control systems for regulating a nonlinear system
2. Design and implement systems to improve nonlinear system performance in the presence of constraints
3. Design and implement observers and estimators for nonlinear systems
4. Configure, implement and test Nonlinear Model Predictive Controllers for simple nonlinear systems
Content
This course will cover:
- Introduction/review of digital control
- Nonlinear systems, basic definitions and comparisons with linear systems
- Linearisation and control of linear systems
- Antiwindup design
- Simplified forms of Feedback linearization
- Output regulation
- Nonlinear Model Predictive Control
- Luenberger observers
- High gain observers
- Nonlinear Kalman Filtering
- Overview of particle filter methods
Assumed knowledge
MATH2310 Calculus of Science and Engineering
and either:
ENGG3440 Linear Control and Estimation or
AERO3600 Embedded Control Systems.
Assessment items
Written Assignment: Assignments
Tutorial / Laboratory Exercises: Laboratory Assignments
Contact hours
Callaghan
Laboratory
Face to Face On Campus 2 hour(s) per Week for Full Term
Lecture
Face to Face On Campus 4 hour(s) per Week for Full Term
The University of Newcastle acknowledges the traditional custodians of the lands within our footprint areas: Awabakal, Darkinjung, Biripai, Worimi, Wonnarua, and Eora Nations. We also pay respect to the wisdom of our Elders past and present.