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

DOI10.1016/j.neunet.2020.10.005zbMath1484.70004OpenAlexW3093636714WikidataQ100961661 ScholiaQ100961661MaRDI QIDQ2055058

Xinyu Zhang, Ning Tan, Tao Wang, Peng Yu

Publication date: 3 December 2021

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2020.10.005

zbMATH Keywords

feedbackrecurrent neural networkmodel-freecontinuum robotszeroing neurodynamics

Mathematics Subject Classification ID

Automated systems (robots, etc.) in control theory (93C85) Control of mechanical systems (70Q05) Kinematics of mechanisms and robots (70B15)

Related Items (3)

Recurrent neural networks as kinematics estimator and controller for redundant manipulators subject to physical constraints ⋮ Discrete‐time extended state observer‐based model‐free adaptive sliding mode control with prescribed performance ⋮ Distributed time-varying optimization control protocol for multi-agent systems via finite-time consensus approach

Cites Work

• Design, verification and robotic application of a novel recurrent neural network for computing dynamic Sylvester equation
• A new noise-tolerant and predefined-time ZNN model for time-dependent matrix inversion
• Zhang Functions and Various Models
• Noise-Tolerant ZNN Models for Solving Time-Varying Zero-Finding Problems: A Control-Theoretic Approach
• Zeroing Dynamics, Gradient Dynamics, and Newton Iterations
• Kinematics and the Implementation of an Elephant's Trunk Manipulator and Other Continuum Style Robots

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