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 |
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Rok vydání: | 2022 |
Předmět: | |
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: |