Model-free motion control of continuum robots based on a zeroing neurodynamic approach

  • Ning Tan*
  • , Peng Yu
  • , Xinyu Zhang
  • , Tao Wang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

As a result of inherent flexibility and structural compliance, continuum robots have great potential in practical applications and are attracting more and more attentions. However, these characteristics make it difficult to acquire the accurate kinematics of continuum robots due to uncertainties, deformation and external loads. This paper introduces a method based on a zeroing neurodynamic approach to solve the trajectory tracking problem of continuum robots. The proposed method can achieve the control of a bellows-driven continuum robot just relying on the actuator input and sensory output information, without knowing any information of the kinematic model. This approach reduces the computational load and can guarantee the real time control. The convergence, stability, and robustness of the proposed approach are proved by theoretical analyses. The effectiveness of the proposed method is verified by simulation studies including tracking performance, comparisons with other three methods, and robustness tests.

Original languageEnglish
Pages (from-to)21-31
Number of pages11
JournalNeural Networks
Volume133
DOIs
StatePublished - Jan 2021

Keywords

  • Continuum robots
  • Feedback
  • Model-free
  • Recurrent neural network
  • Zeroing neurodynamics

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