Fuzzy Dual-Hunting Control Based on Auction Algorithm

In this paper, a fuzzy dual-hunting control based on auction algorithm is proposed. Relying on a single containment gives the small target the possibility of escape. Therefore, we design a dual-hunting framework for multiagent systems to hunt a small target. A hunting formation with double containment is designed to reduce the possibility of the target escaping. Then, an auction algorithm is designed to generate the desired formation and rationally plan the positions of the agents in the hunting formation. To improve the applicability of the dual-hunting framework, we take high-order multiagent systems as the research object, and the fuzzy logic system (FLS) is introduced to approximate the unknown nonlinear dynamics (UND) due to higher-order system model errors and environmental disturbances. Based on FLS and backstepping method, a hunting controller for high-order systems is designed, which enables multiagent systems to track targets and form hunting formations. Furthermore, the Lyapunov function is designed to prove the stability of the controller. Finally, the effectiveness of the proposed method is demonstrated by simulating a multiagent system containing 12 intelligences hunting for a dynamic target.