Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Task and Spatial Planning by the Cognitive Agent with Human-Like Knowledge Representation Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Hybrid Force/Position Control of a Collaborative Parallel Robot Using Adaptive Neural Network

Authors : Seyedhassan Zabihifar, Arkadi Yuschenko

Published in: Interactive Collaborative Robotics

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In this paper, a new stable adaptive neural network control scheme has been presented for hybrid position and force control of the Delta parallel robot. Force control is an important technique in programming and safety for collaborative robots. The hybrid control scheme is introduced to tackle the interaction problem between the robot and its environment such that the robot follows the position trajectory and desired force, which is applied in a certain position. The goal of the control is applying desired force trajectory in a certain position in which there is a constraint for movement. Fewer parameter settings, adaptive algorithm, and efficient control input signals are the advantages of the proposed controller.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Multi-agent Robotic Systems in Collaborative Robotics
next chapter Swarm Robotics: Remarks on Terminology and Classification
Literature
1.
Magrini, E., De Luca, A.: Hybrid force/velocity control for physical human-robot collaboration tasks. In: EEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), pp. 857–863. IEEE (2016)
2.
Tanaka, Y., Tsuji, T.: On-line learning of robot arm impedance using neural networks. In: IEEE International Conference on Robotics and Biomimetics, pp. 941–946 (2004)
3.
Singh, H.P., Sukavanam, N., Panwar, V.: Neural network based compensator for robustness to the robot manipulators with uncertainties. In: Proceedings of the International Conference on Mechanical and Electrical Technology, ICMET 2010, pp. 444–448 (2010)
4.
Moreno-Valenzuela, J., Aguilar-Avelar, C.S., Puga-Guzman, A., Santibanez, V.: Adaptive neural network control for the trajectory tracking of the Furuta pendulum. IEEE Trans. Cybern. 46(12), 3439–3452 (2016)CrossRef
5.
Khazaee, M., Markazi, A.H.D., Rizi, S.T., Seyfi, B.: Adaptive fuzzy sliding mode control of input-delayed uncertain nonlinear systems through output-feedback. Nonlinear Dyn. 87(3), 1943–1956 (2017)CrossRef
6.
Van Cuong, P., Nan, W.Y.: Adaptive trajectory tracking neural network control with robust compensator for robot manipulators. Neural Comput. Appl. 27(2), 525–536 (2016)CrossRef
7.
Codourey, A.: Dynamic modelling and mass matrix evaluation of the DELTA parallel robot for axes decoupling control. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 1996), vol. 3, pp. 1211–1218 (1996)
8.
Du, J., Lou, Y.: Simplified dynamic model for real-time control of the delta parallel robot. In: IEEE International Conference on Information and Automation (ICIA 2016), pp. 1647–1652. IEEE (2016)
9.
Slotin, E.: Applied Nonlinear Control. Prentice Hall, New Jersey (1991)
10.
Hana Boudjedir, N.R., Yacef, F., Bouhali, O.: Dual neural network for adaptive sliding mode control of quadrotor helicopter stabilization. Int. J. Inf. Sci. Tech. 2(4), 101–115 (2012)
11.
12.
Lewis, F.L., Jaganathan, S., Yesildirek A.: Neural network control of robot manipulators and nonlinear systems (1999)
Metadata
Title
Hybrid Force/Position Control of a Collaborative Parallel Robot Using Adaptive Neural Network
Authors
Seyedhassan Zabihifar
Arkadi Yuschenko
Copyright Year
2018
Book
Interactive Collaborative Robotics

Print ISBN: 978-3-319-99581-6

Electronic ISBN: 978-3-319-99582-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-99582-3_29

Premium Partner

    Image Credits