- author = "Mathias Tantau and Lars Perner and Mark Wielitzka and Tobias Ortmaier",
- editor = "Oleg Gusikhin and Kurosh Madani and Janan Zaytoon",
- title = "Structure and Parameter Identification of Process Models with Hard Non-linearities for Industrial Drive Trains by Means of Degenerate Genetic Programming",
- booktitle = "Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2019",
- year = "2019",
- volume = "1",
- pages = "368--376",
- publisher = "SciTePress",
- month = jul # " 29-31",
- address = "Prague, Czech Republic",
- keywords = "genetic algorithms, genetic programming, Modelling, Simultaneous Identification of Structure and Parameters, Phenomenological Models, Backlash, Multiple-mass Resonators, Artificial Intelligence, Computational Intelligence, Evolutionary Computation and Control, Evolutionary Computing, Informatics in Control, Automation and Robotics, Intelligent Control Systems and Optimization, Optimization Algorithms, Soft Computing",
- isbn13 = "978-989-758-380-3",
- ISSN = "2184-2809",
-
URL = "
https://www.repo.uni-hannover.de/handle/123456789/10472",
-
URL = "https://doi.org/10.5220/0007949003680376",
-
DOI = "
doi:10.5220/0007949003680376",
- timestamp = "Wed, 18 Sep 2019 16:30:21 +0200",
-
biburl = "https://dblp.org/rec/conf/icinco/TantauPWO19.bib",
- bibsource = "dblp computer science bibliography, https://dblp.org",
- size = "9 pages",
- abstract = "The derivation of bright-grey box models for electric drives with coupled mechanics, such as stacker cranes, robots and linear gantries is an important step in control design but often too time-consuming for the ordinary commissioning process. It requires structure and parameter identification in repeated trial and error loops. In this paper an automated genetic programming solution is proposed that can cope with various features, including highly non-linear mechanics (friction, backlash). The generated state space representation can readily be used for stability analysis, state control, Kalman filtering, etc. This, however, requires several special rules in the genetic programming procedure and an automated integration of features into the defining state space form. Simulations are carried out with industrial data to investigate the performance and robustness.",
-
notes = "p372 'Each node is assigned a model type and the
number of nodes with a certain model type defines the
multiplicity of this submodel. Connections between
nodes do not represent the flow of information but
merrily the genetic connection as bases on a
chromosome,'
Crossover, cloning, Point mutation, insertion mutation, deletion mutation, chromosome mutation",
