Distributed Bearing-Only Formation Control for UAV-UWSV Heterogeneous System

Abstract

This paper investigates the bearing-only formation control problem of a heterogeneous multi-vehicle system, which includes unmanned aerial vehicles (UAVs) and unmanned surface vehicles (UWSVs). The interactions among vehicles are described by a particular class of directed and acyclic graphs, namely heterogeneous leader-first follower (HLFF) graphs. Under the HLFF structure, a UAV is selected as the leader, moving with the reference dynamics, while the followers, including both UAVs and UWSVs, are responsible for controlling the position with regard to the neighbors in the formation. To solve the problem, we propose a velocity-estimation-based control scheme, which consists of a distributed observer for estimating the reference velocity of each vehicle and a distributed formation control law for achieving the desired formation based on the estimations and bearing measurements. Moreover, it is shown that the translation and scale of the formation can be uniquely determined by the leader UAV. The theoretical analysis demonstrated the finite-time convergence of the velocity estimation and the asymptotic convergence of the formation tracking. Comparative simulation results are provided to substantiate the effectiveness of the proposed method.

Strategic Control in Cooperative Multi-Agent Moving Source Seeking with Obstacles Avoidance

“…where 𝒈 ̂(𝑟 𝑖 ) is the estimated gradient calculated by agent 𝑖. 𝑏 𝑖 = 𝐴 𝑖 𝑔 ̂𝑖 (7) where 𝑏 𝑖  ℝ |𝑁 𝑖 |1 , 𝐴 𝑖  ℝ ||𝑁 𝑖 ||𝑝 , and 𝒈 ̂𝒊  ℝ 𝑝1 . This problem can be solved by using the least-squares method…”

“…In multi-agent systems, formation control is an important theme to study [5][6][7][8] because it is often used in the military and civil fields. A group of UAVs will face greater challenges when carrying out complex tasks.…”

Formation Control for UAV-USVs Heterogeneous System with Collision Avoidance Performance

“…This is accomplished by harnessing the combined strengths of adaptive methodologies and Radial Basis Function (RBF) neural networks. In [26], the research proposes a velocity estimationbased control strategy that comprises a distributed observer for estimating each vehicle's reference velocity. In [23], a distributed model predictive control algorithm tailored for heterogeneous systems is presented, characterized by a directed topological structure.…”

“…(1) Compared with the existing results in [12,[29][30][31], which only study the cooperative trajectory tracking problem of UAV and USV heterogeneous systems, this paper explores the collision avoidance protocol for USV formation under UAV cooperation with navigation practice. (2) Compared with the existing results in [18,25,26,32], which estimate that the system's indeterminate terms rely on RBF neural networks and fuzzy logic, etc., this paper employs ESO to realize the accurate compensation of uncertainties and external disturbances in heterogeneous systems. (3) Compared with the existing results in [31][32][33][34][35][36][37], this paper innovatively introduces the ship encounter situation and danger evaluation index into the APF approach, and the improved APF method for heterogeneous cooperative control collision avoidance decision is more in line with the navigation practice.…”

Research on pure azimuth passive positioning of UAV based on iterative algorithm

“…Thousands of drones in formation [2] , countless "fireflies" light up the night sky, has become an independent business model, will continue to expand the impact. In order to maintain the formation, it is proposed to adjust the position of UAVs by pure orientation passive positioning [3], i.e., a few UAVs in the formation transmit signals [4] and the rest passively receive signals, from which directional information is extracted for positioning [5]to adjust the position of UAVs. Each UAV in the formation has a fixed number, and the relative position relationship with other UAVs in the formation remains unchanged.…”