Do you also have a system that has the same error for each task? This course enables you to improve the performance of your system by advanced feedforward and learning control. In recent years, classical feedback controllers and feedforward controllers have been further developed towards advanced feedforward. These developments include iterative learning control, which applies to industrial systems, including pick-and-place machines or batch processes, that perform the same task over and over again. When exactly the same task is performed, disturbances act on the system identically over the tasks.
Think, for instance, about a disturbance torque profile, from unbalance in an axis, or from unknown friction effects. The key idea is that iterative learning control can completely compensate for these disturbances, leading to a typical order of magnitude reduction of servo errors.
Read the interview with lecturer Dr. ir. Tom Oomen ‘Iterative learning control improves the performance of motion systems by a factor of ten’:
- in Dutch
- in English
Iterative learning control is able to achieve exceptional performance for exactly repeating tasks. However, iterative learning control cannot deal with varying tasks. Even a small variation can lead to disastrous performance deterioration. Many industrial systems perform such very similar yet slightly different tasks, necessitating new concepts for advanced feedforward control, including high-order feedforward (snap, jerk, etc.), input shaping, automated tuning, etc. These new concepts have been developed in recent years, whereas most of these 'iterative learning control' (ILC) techniques have been developed in the past two decades and many successful industrial applications have been reported.
This new and extended course starts by recapitulating classical feedforward, and covers an in-depth treatment of iterative learning control, repetitive control, and new advanced feedforward approaches. The course covers:
€ 2.245,00 excl. VAT
3 consecutive days
How participants recommend this training to others:
(average score of last 3 editions)
09-10-2019 | 09:00 - 17:00
10-10-2019 | 09:00 - 17:00
11-10-2019 | 09:00 - 17:00
After attending this course, participants are enabled to:...
After attending this course, participants are enabled to:
This course is intended for engineers involved in control systems who want to gain more insight i...
This course is intended for engineers involved in control systems who want to gain more insight into the possibilities and implementations of advanced feedforward and learning control in an industrial setting.
It is recommended that participants already have a Bachelor or Master education in electrical engineering, mechanical engineering, mechatronics, physics, or equivalent practical experience and must have some basic understanding of servo control.
This course is particularly suitable for engineers having followed the course in 'Motion control tuning'.
The following topics are treated:...
The following topics are treated:
This course is certified by the European society f...
This course is certified by the European society for precision engineering & nanotechnology (euspen) and the Dutch Society for Precision Engineering (DSPE) and leads to the ECP2-certificate.
'Great atmosphere, good lecturers, well done!'
'Most important items learned: ILC in general. Hands one experiments and experience.'
'Excellent training - one of the best I have ever attended. I enjoyed it very much! Looking forward to implementing some of the concepts learned by our motion controllers.'
'Excellent course. Delivered enthusiastically and strikes the right balance between theory and experiments!'
This course treats the essential basis of control in a modern framework and the participants are trained in applying these techniques theoretically and experimentally to mechatronic servo systems.
Read more →
Follow-up of the basic course 'Motion control tuning'. Focusses on the analysis and control of multi-variable servo systems with in-depth treatment of interaction analysis, decoupling, MIMO-control.
Read more →