Yoo Sung Jin, Park Bong Seok
IEEE Trans Cybern. 2024 Jun;54(6):3431-3443. doi: 10.1109/TCYB.2023.3265405. Epub 2024 May 30.
This article explores a guaranteed network connectivity problem during moving obstacle avoidance within a distributed formation tracking framework for uncertain nonlinear multiagent systems with range constraints. We investigate this problem based on a new adaptive distributed design using nonlinear errors and auxiliary signals. Within the detection range, each agent regards other agents and static or dynamic objects as obstacles. The nonlinear error variables for formation tracking and collision avoidance are presented, and the auxiliary signals in formation tracking errors are introduced to maintain network connectivity under the avoidance mechanism. The adaptive formation controllers using command-filtered backstepping are constructed to ensure closed-loop stability with collision avoidance and preserved connectivity. Compared with the previous formation results, the resulting features are as follows: 1) the nonlinear error function for the avoidance mechanism is considered an error variable, and an adaptive tuning mechanism for estimating the dynamic obstacle velocity is derived in a Lyapunov-based control design procedure; 2) network connectivity during dynamic obstacle avoidance is preserved by constructing the auxiliary signals; and 3) owing to neural networks-based compensating variables, the bounding conditions of time derivatives of virtual controllers are not required in the stability analysis.
本文探讨了具有范围约束的不确定非线性多智能体系统在分布式编队跟踪框架内进行移动障碍物避障时的网络连通性保障问题。我们基于一种使用非线性误差和辅助信号的新型自适应分布式设计来研究该问题。在探测范围内,每个智能体将其他智能体以及静态或动态物体视为障碍物。给出了用于编队跟踪和避碰的非线性误差变量,并引入编队跟踪误差中的辅助信号,以在避障机制下维持网络连通性。构建了使用指令滤波反步法的自适应编队控制器,以确保闭环稳定性并实现避碰和保持连通性。与先前的编队结果相比,所得特性如下:1)将避障机制的非线性误差函数视为误差变量,并在基于李雅普诺夫的控制设计过程中推导了用于估计动态障碍物速度的自适应调整机制;2)通过构建辅助信号来保持动态避障期间的网络连通性;3)由于基于神经网络的补偿变量,在稳定性分析中不需要虚拟控制器时间导数的有界条件。