Gradient-Free Cooperative Source-Seeking of Quadrotor Under Disturbances and Communication Constraints
Zhenghong Jin, Hua Li, Zhengyan Qin, Zhanxiu Wang
Abstract
This article presents a novel design algorithm for the cooperative source-seeking problem using a group of quadrotors equipped with sensors for source scalar field measurement with limited communications. The main objective is to drive the average position state of quadrotors to the optimal point of a given scalar field function while maintaining the desired formation, based on the field value measured by each quadrotor. To achieve this objective, the formation-based source-seeking algorithm is proposed with a cascade structure and the consensus filter, which is composed of a formation controller and a gradient-free optimization algorithm: the formation controller implements the desired formation and provides optimization direction information for the optimization algorithm, while the optimization algorithm generates a movement direction to guide the average position state of quadrotors collectively moving toward the source without estimating gradient, and the consensus filters estimate the centralized quantities. The Lyapunov stability analysis and invariancelike theorem are applied to establish the convergence and robustness of quadrotors’ positions and velocities to the formation and the average position to the optimal point. Finally, the effectiveness of the proposed method is illustrated by a physical experiment and a numerical simulation.