Pneumatic Artificial Muscle-Driven Control Loading System (iFUZZY2017)

Chun Ta Chen, Yu Cheng Wu, Fu Wen Chen, Mei Yung Chen

Research output: Contribution to journalArticle

Abstract

A control loading system (CLS) provides a force feel about the state of devices. In this paper, the technique for a pneumatic artificial muscle (PAM)-actuated control loading system is developed. The proposed PAM-based control loading system is made with a steel string fixed at one end and the other end connected to a control column, and a force feedback to an operator can be achieved according to the system state. In order to demonstrate the dynamic force feedback characteristics, a second-order mass-spring-damper model is used for the computed force, and the force control is implemented via the position-loop architecture. Moreover, due to the structure and parametric uncertainties of the designed control loading system, the adaptive fuzzy sliding mode controller are employed to improve the fidelity feeling of the force exerted on the control column. Benchmark tests compare the adaptive fuzzy sliding mode controller with other controllers. Results demonstrate the designed PAM-driven control loading system.

Original languageEnglish
Pages (from-to)1779-1789
Number of pages11
JournalInternational Journal of Fuzzy Systems
Volume20
Issue number6
DOIs
Publication statusPublished - 2018 Aug 1

Fingerprint

Artificial muscle
Pneumatics
Muscle
Force Feedback
Sliding Mode
Controller
Controllers
Feedback
Force Control
Parametric Uncertainty
Damper
Force control
Taiwan
Fuzzy systems
Fuzzy Systems
Fidelity
Demonstrate
Steel
Strings
Benchmark

Keywords

  • Adaptive fuzzy sliding mode control
  • Control loading system
  • Pneumatic artificial muscle

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

Cite this

Pneumatic Artificial Muscle-Driven Control Loading System (iFUZZY2017). / Chen, Chun Ta; Wu, Yu Cheng; Chen, Fu Wen; Chen, Mei Yung.

In: International Journal of Fuzzy Systems, Vol. 20, No. 6, 01.08.2018, p. 1779-1789.

Research output: Contribution to journalArticle

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