A computational method to find the optimal driving-path for stable state transformation of multistable tensegrity

Abstract

This paper introduces a computational approach for identifying the optimal driving-path for stable state transformations (SST) of multistable tensegrity structures. In order to capture the morphological changes of the tensegrity structure when the driving-nodes are actuated along arbitrary driving-path, a tracking method is firstly introduced. Then, the concept of segmenting-nodes is introduced to parameterize the driving-path. With the coordinates of segmenting-nodes on driving-path as optimization variables and the minimum energy threshold in the process of SST as objective function, a nonlinear optimization model is established and solved by particle swarm optimization algorithm. The feasibility of the proposed method is verified by three multistable tensegrity examples with different scales. In addition, the proposed method is compared with two existing methods, and the results further prove that the proposed method has the advantages of simple driving scheme and low energy threshold. The research provides instructive significance for the practical application of multistable tensegrity.