Optimal design of an autonomous underwater helicopter's shape based on combinatorial optimization strategy

Abstract

In this study, the shape of the autonomous underwater helicopter (AUH) was optimized. AUH is a new type of disc autonomous underwater vehicle with good maneuverability and flexibility. In this paper, an optimization mathematical model is established, which takes the resistance coefficient as the optimization objective and the internal volume and the actual engineering demand as the constraints. The optimization mathematical model of AUH is solved by using two combinatorial optimization strategies. Two combinatorial optimization strategies use experimental design algorithm and multi Island genetic algorithm (MIGA) as global search algorithm, and sequential quadratic programming algorithm as local search algorithm. And based on the back propagation (BP) neural network, the sample points are trained and fitted, and the cloud map of the resistance coefficient distribution in the design space is obtained. The optimization results show that compared with the initial resistance coefficient, the first optimal solution reduces by 9.14%, and the second optimal solution reduces by 9.53%. So the resistance performance of AUH is significantly improved, which proves the feasibility of the method proposed in this paper. This provides theoretical support for the shape optimization design of AUH, which will improve the motion performance of AUH in practical engineering applications.