Gaussian Process Position-Dependent Feedforward: With Application to a Wire Bonder

Autor:	van Haren, Max, Poot, Maurice, Kostić, Dragan, van Es, Robin, Portegies, Jim, Oomen, Tom
Rok vydání:	2022
Předmět:	Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
DOI:	10.1109/AMC51637.2022.9729327
Popis:	Mechatronic systems have increasingly stringent performance requirements for motion control, leading to a situation where many factors, such as position-dependency, cannot be neglected in feedforward control. The aim of this paper is to compensate for position-dependent effects by modeling feedforward parameters as a function of position. A framework to model and identify feedforward parameters as a continuous function of position is developed by combining Gaussian processes and feedforward parameter learning techniques. The framework results in a fully data-driven approach, which can be readily implemented for industrial control applications. The framework is experimentally validated and shows a significant performance increase on a commercial wire bonder. Comment: in IEEE 17th International Conference on Advanced Motion Control, Padova, Italy, 2022
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2201.07511 Zobrazit plný text záznamu View this record from Arxiv