Model-Based and Markov Data-Based Linearized Tensegrity Dynamics and Analysis of Morphing Airfoils

Muhao Chen, Yuling Shen, Robert E. Skelton

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This paper introduces two methods for linearizing nonlinear tensegrity dynamics: a model based and a Markov data-based approach. We first give the tensegrity notations and their nonlinear dynamics, followed by the theoretical formulation of a model-based linearization using Taylor expansion. Subsequently, the paper presents an empirical method of Markov data-based approach to linearizing these dynamics. Finally, we implement a shape-controllable tensegrity airfoil as an example. An extensive study and analysis are provided to compare the efficacy of both linearization methods. The principles established in this research are applicable to a variety of structures beyond tensegrity.

Original languageEnglish
Title of host publicationAIAA SciTech Forum and Exposition, 2024
DOIs
StatePublished - 2024
EventAIAA SciTech Forum and Exposition, 2024 - Orlando, United States
Duration: Jan 8 2024Jan 12 2024

Publication series

NameAIAA SciTech Forum and Exposition, 2024

Conference

ConferenceAIAA SciTech Forum and Exposition, 2024
Country/TerritoryUnited States
CityOrlando
Period1/8/241/12/24

Bibliographical note

Publisher Copyright:
© 2024 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

ASJC Scopus subject areas

  • Aerospace Engineering

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