Model generation and parameter identification of unknown environment using element description method

Issei Takeuchi, Seiichiro Katsura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an identification method of unknown environment for motion control. The proposed method can estimate a physical model and its parameter simultaneously by using element description method. In this paper, the proposed method is applied to identification of environmental characteristics. General identification methods need to decide a physical model of target in advance. In another approaches such as neural network and black-box modeling methods by database, notwithstanding achieving input-output characteristics, these methods are difficult to understand the physical meaning of target environment. On the contrary, the proposed method can identify not only parameter but also a physical model of environment, which is the merit of the proposed method. Also the physical meaning of target environment is understandable according to element description. By using the proposed method, ideal controller for contact task can be designed based on environmental model and its parameter. It may be possible to discover a new physical property of environment.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages330-335
Number of pages6
ISBN (Electronic)9781509045389
DOIs
Publication statusPublished - 2017 May 6
Event2017 IEEE International Conference on Mechatronics, ICM 2017 - Gippsland, Australia
Duration: 2017 Feb 132017 Feb 15

Other

Other2017 IEEE International Conference on Mechatronics, ICM 2017
CountryAustralia
CityGippsland
Period17/2/1317/2/15

Fingerprint

Parameter Identification
Identification (control systems)
Unknown
Physical Model
Motion control
Model
Target
Physical properties
Neural networks
Characteristics Method
Controllers
Motion Control
Black Box
Modeling Method
Physical property
Contact
Neural Networks
Controller
Output
Estimate

Keywords

  • element description
  • genetic algorithm
  • Motion control
  • system identification

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

Cite this

Takeuchi, I., & Katsura, S. (2017). Model generation and parameter identification of unknown environment using element description method. In Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017 (pp. 330-335). [7921126] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMECH.2017.7921126

Model generation and parameter identification of unknown environment using element description method. / Takeuchi, Issei; Katsura, Seiichiro.

Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 330-335 7921126.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Takeuchi, I & Katsura, S 2017, Model generation and parameter identification of unknown environment using element description method. in Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017., 7921126, Institute of Electrical and Electronics Engineers Inc., pp. 330-335, 2017 IEEE International Conference on Mechatronics, ICM 2017, Gippsland, Australia, 17/2/13. https://doi.org/10.1109/ICMECH.2017.7921126
Takeuchi I, Katsura S. Model generation and parameter identification of unknown environment using element description method. In Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 330-335. 7921126 https://doi.org/10.1109/ICMECH.2017.7921126
Takeuchi, Issei ; Katsura, Seiichiro. / Model generation and parameter identification of unknown environment using element description method. Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 330-335
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