A Genetic Algorithm Approach for 2-D Tensegrity Form Finding

Abstract

This paper presents a novel and versatile method for finding 2-D tensegrity structures form finding. Using this method, different possibilities for the geometry of 2-D tensegrity structures can be found with little information about the structure. As opposed to most existing procedures this method only needs the number of each member prototype, the number of tensegrity nodes and connectivity at each node to be known. The form finding is done by minimizing objective function, which considers the rank deficiencies of the geometry, the prestress coefficients and the semi-positive definite condition of the stiffness matrix. Genetic algorithm as the global search is taken into account first for generating the connectivity matrix, initial prestress coefficients and also minimizing the objective function. Several numerical examples are given to demonstrate the competence and robustness of the current study in searching new different possibility self-equilibrium configuration of tensegrity structures.