Design of a single-DOF kinematic chain using hybrid GA-pattern search and sequential GA

With the aim of obtaining an optimal design for a single-DoF kinematic chain with the function of morphing aerofoils, two search methods are developed. The assessment criteria are the length of the linkage and the accuracy of mapping. While the former is taken as the objective of optimization, the latter is treated as a constraint. The accuracy in mapping is measured by the aerodynamic performance deviation, a parameter defined by combining the geometric deviation and a weighting function based on the distribution of pressure coefficient. The first search method is based on a genetic algorithm (GA) with an embedded pattern search algorithm. The aim of the pattern search is to reduce the number of failed attempts in generating feasible solutions for the initial population of the GA as well as repairing infeasible individuals produced by reproduction operators. In the second search method, the set of design variables is determined in two consecutive steps by employing a sequential GA. Results of five runs of each search method reveal that while the best solution was produced by the sequential GA search method, hybrid GA-pattern search yielded more consistent results with shorter lengths and better mapping precision in average.