Mixed game pigeon-inspired optimization for unmanned aircraft system swarm formation

Abstract

This paper proposes a novel mixed game pigeon-inspired optimization (MGPIO) algorithm for unmanned aircraft system (UAS) swarm formation control. The outer loop controller based on artificial potential field method is designed to transform the UAS swarm formation into abstract movements in the potential field. The inner loop controller based on PIO is designed to solve the optimal UAS position. A novel pigeon-inspired optimization integrated with mixed game theory is proposed to enhance its capacity and convergence speed to solve complex problem while reducing the computational load. This method maintains the capability of the PIO to diversify the pigeons’ exploration in the solution space. Moreover, the proposed method improves the quality of the pigeons based on the situation. A series of simulation experiments are conducted compared with basic PIO and Particle Swarm Optimization (PSO) approach. The experimental results verify the feasibility and effectiveness of the proposed method.