KALMAN FILTERs for Chemical engineers and metallurgists
Enrol Now for Exclusive Access
Join our comprehensive course designed for chemical and metallurgical engineers eager to master Kalman filter applications in their field.
Gain practical insights and hands-on experience to enhance your process engineering skills.
Bring your own technical problem in Day 3 and work on it alongside our experts!
40+
Years of Expertise Offered
3
Course Duration in Days
Course Details
The Kalman filter is a powerful mathematical tool widely used in many engineering fields, but relatively unknown in chemical and metallurgical engineering. This course is designed to provide chemical and metallurgical engineers with a comprehensive understanding of Kalman filter applications, enabling them to enhance their data analysis and control systems skills. Participants will learn in a “hands-on”, practical and solution-driven environment where the course presenters provide support and guidance and learners are free to advance at their own pace. The number of participants is strictly limited to ensure that everyone receives the support they require.
All examples in the course use Excel (with macros) so the example solutions require no special software and can be understood easily. For portability, the solutions will also be provided in MATLAB and Python that can be downloaded from our course website.
The curriculum covers essential topics such as state estimation, system modeling, and filter tuning. More advanced topics such as non-linearity, intermittent sampling, complex modelling and detecting measurement errors are also covered. By the end of the course, participants will have gained the confidence to implement Kalman filters in their projects, leading to improved decision-making and operational efficiency.
On the third day of the course, participants are welcome to bring their own real-world problems and tackle these with guidance from our expert course leaders.
All course participants receive links to Excel, MATLAB and Python code developed in the course along with further resources for ongoing support.
Join us in this enriching learning experience tailored for chemical and metallurgical engineers eager to advance their expertise with Kalman filters. With a focus on practical skills and real-world scenarios, this course promises to equip you with the knowledge necessary to excel in your field. Enrol today and take the first step towards mastering this essential engineering tool!
Day 1 Highlights
- Examples of good Kalman filter applications for Chemical and Metallurgical processes
- Alternatives to the Kalman filter – when is it better and when not?
- Process models, measurement noise and tuning – how Kalman filters work in real world applications
- Kalman filter in-class worked practical example
- Industrial Example 1: using a Kalman filter to estimate an unknown process measurement
- Kalman filter theory summary: why it works and where it doesn’t
Day 2 Highlights
- Industrial Example 2: Using a Kalman filter to Predict a Process Measurement
- Industrial Example 2: Assessment and review
- Improving our predictions by changing the design of a Kalman filter
- Dealing with Intermittent Measurements, Non-linearities and Noise – Industrial Example 3
Day 3 Highlights
- Option 1 – BYO Problem: Participants work on their own real-world problems with guidance from course presenters
- Option 2 – Industrial Examples 4 and 5: Finding Process Measurement Errors
- Option 3 – Industrial Example 6: Finding and Correcting Errors in Multiple Measurement Systems
- Kalman filter theory summary and takeaway Kalman filter cheat sheet
Course Presenters
Dr. Andrew A. Shook
Independent Consultant
Andrew has a B.E. degree in Chemical Engineering and MASc. and PhD degrees in Metallurgical Engineering.
Andrew has more than twenty years’ experience developing and deploying mathematical models to improve industrial process systems.
After senior technical roles in BHP and Rio Tinto, Andrew is now an independent consultant providing specialist process support to several industrial clients.
A skilled communicator with many years of experience, Andrew will guide you through the core process applications of Kalman filters through worked examples.
Dr. Liuping Wang
Professor of Control Engineering, RMIT
Liuping obtained her PhD degree from the University of Sheffield in the field of automatic control. She is an electrical engineer by training but has substantial experience in the area of chemical process control. Liuping is the author of four textbooks on model predictive control, PID control, state feedback control and Kalman filtering.
With deep theoretical knowledge, Liuping adds to Andrew’s practical approach and is able to provide course attendees with strong guidance through the mathematical complexities of Kalman filter development and application.