Trajectory-tracking of 6-RSS Stewart-Gough manipulator by feedback-linearization control using a novel inverse dynamic model based on the force distribution algorithm Article Swipe
Zafer Mahmoud
,
Mohammad Reza Arvan
,
Vahab Nekoukar
,
Mohammad Rezaei
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1080/13873954.2020.1754861
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1080/13873954.2020.1754861
6-RSS Stewart-Gough parallel manipulator contains six crank-rod limbs connecting the base and moving platforms to each other, forming a 6DOF manipulator. In this paper, we introduce a novel decoupled inverse dynamic model for this manipulator based on the Force Distribution Algorithm. The performance of the proposed model was evaluated in tracking a complex trajectory (of multiple segments with simultaneous translational and rotational motions) using feedback-linearization control in the joint space and compared with that of the Lagrangian inverse dynamic model. Results showed that this model leads to a better performance in feedback-linearization control, especially when the reference trajectory is quantized, and with less calculation burden in comparison with the Lagrangian model. The control system employing both models showed robustness against payload uncertainty on the moving platform (150% of the moving platform’s mass). The performance assessment and the robustness approval were performed in simulation using a Simscape model specifically built for this purpose in the Simulink environment.
Related Topics
Concepts
Control theory (sociology)
Robustness (evolution)
Feedback linearization
Stewart platform
Inverse dynamics
Linearization
Inverse
Computer science
Trajectory
Payload (computing)
RSS
Mathematics
Artificial intelligence
Nonlinear system
Control (management)
Kinematics
Physics
Chemistry
Geometry
Classical mechanics
Operating system
Computer network
Gene
Network packet
Biochemistry
Astronomy
Quantum mechanics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/13873954.2020.1754861
- https://www.tandfonline.com/doi/pdf/10.1080/13873954.2020.1754861?needAccess=true
- OA Status
- bronze
- Cited By
- 4
- References
- 29
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3031241408
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3031241408Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1080/13873954.2020.1754861Digital Object Identifier
- Title
-
Trajectory-tracking of 6-RSS Stewart-Gough manipulator by feedback-linearization control using a novel inverse dynamic model based on the force distribution algorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-05-03Full publication date if available
- Authors
-
Zafer Mahmoud, Mohammad Reza Arvan, Vahab Nekoukar, Mohammad RezaeiList of authors in order
- Landing page
-
https://doi.org/10.1080/13873954.2020.1754861Publisher landing page
- PDF URL
-
https://www.tandfonline.com/doi/pdf/10.1080/13873954.2020.1754861?needAccess=trueDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://www.tandfonline.com/doi/pdf/10.1080/13873954.2020.1754861?needAccess=trueDirect OA link when available
- Concepts
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Control theory (sociology), Robustness (evolution), Feedback linearization, Stewart platform, Inverse dynamics, Linearization, Inverse, Computer science, Trajectory, Payload (computing), RSS, Mathematics, Artificial intelligence, Nonlinear system, Control (management), Kinematics, Physics, Chemistry, Geometry, Classical mechanics, Operating system, Computer network, Gene, Network packet, Biochemistry, Astronomy, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2022: 1, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
29Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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