Data-based hybrid modelling of the component placement process in pick-and-place machines
By Aleksandar Lj. Juloski, W. M. Heemels, Giancarlo Ferrari-Trecate. 2004
71 citations recorded by the source corpus.
In this paper, an experimental study in the identification of the electronic component placement process in pick-and-place machines is presented. Unilateral contact and saturation phenomena characterize the hybrid dynamics of the system. Furthermore, the mode switch cannot be measured and identification algorithms for hybrid systems, that are capable of reconstructing both the modes and the switching law, must be used. Piece-wise autoregressive exogenous (PWARX) models, which consist of a number of ARX modes together with the partition of the regressor space into regions where each model is valid are identified. Reconstructed models are able to capture the relevant dynamics of the experimental setup. Practical insights on hybrid system identification and comments on possible improvements of the identification algorithm complement the quantitative results.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/baedb55b514e93aadf3970d7ee2caffd2079b4aa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Simone Paoletti
- Aleksandar Lj. Juloski
- René Vidal
- Giancarlo Ferrari-Trecate
- Alberto Bemporad
- W. M. Heemels
- Antonio Vicino
- Andrea Garulli
Citations in the corpus
- A bounded-error approach to piecewise affine system identification (2005, methodology): “The reader is referred to [22] for a more detailed description of the experimental setup.”
- Identification of Hybrid Systems: A Tutorial (2007, methodology): “These techniques have been successfully applied in real problems, such as identification of the electronic component placement process in pick-and-place machines [5, 43, 47], modelling of a current transformer [27], traction control [11], and motion segmentation in computer vision [76, 77].”
- A Bayesian approach to identification of hybrid systems (2004, methodology): “The need for using a priori knowledge was observed in an experimental case study of a component placement process in a pick-and-place machine [17], [18].”