{"title":"高阶非线性多代理系统的实用时变编队协同控制,通过安全约束避免空间资源冲突","authors":"Xiaoshan Ma, Tawei Chou","doi":"10.1002/rnc.7600","DOIUrl":null,"url":null,"abstract":"The operation of multi‐agent systems (MAS) in space necessitates considerations for obstacle avoidance, collision prevention, and connectivity among agents. This coupling conflict, stemming from spatial resource utilization, poses a significant and non‐negligible threat to the safe operation of MAS. This article proposes a consensus control scheme for the time‐varying formation of MAS, incorporating functions for maintaining connectivity, collision avoidance, and obstacle dodging. This scheme effectively constrains the time‐varying formation tracking error within an arbitrarily small range. The considered system model takes a high‐order nonlinear form, with uncertainties and disturbances present in each order. This grants the control scheme with high generality and practicability. By employing barrier Lyapunov function to delineate the safe operational space of MAS, conflicts in spatial resource utilization are avoided. This approach simultaneously fulfills the requirements for connectivity maintenance, collision avoidance, and obstacle dodging in the safe operation of MAS. An additional rotation operator is integrated into the controller to smoothly address the “minima” problem, eliminating the need for external intervention. Gaussian radial basis function is used to estimate the nonlinear terms, uncertainties, and unknown perturbation online in the system. The stability of the MAS under the proposed control scheme is analyzed through Lyapunov function. 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引用次数: 0
摘要
多代理系统(MAS)在空间中的运行需要考虑避障、防碰撞以及代理之间的连接。这种因空间资源利用而产生的耦合冲突对 MAS 的安全运行构成了不可忽视的重大威胁。本文提出了一种用于 MAS 时变编队的共识控制方案,其中包含维持连接、避免碰撞和躲避障碍的功能。该方案有效地将时变编队跟踪误差限制在一个任意小的范围内。所考虑的系统模型采用高阶非线性形式,每个阶都存在不确定性和干扰。这使得控制方案具有很高的通用性和实用性。通过使用屏障 Lyapunov 函数来划定 MAS 的安全运行空间,可以避免空间资源利用方面的冲突。这种方法同时满足了 MAS 安全运行中的连通性维护、避免碰撞和躲避障碍物的要求。控制器中还集成了一个额外的旋转算子,可顺利解决 "最小值 "问题,无需外部干预。高斯径向基函数用于在线估计系统中的非线性项、不确定性和未知扰动。通过 Lyapunov 函数分析了拟议控制方案下 MAS 的稳定性。最后,通过数值模拟结果来解释控制方案的有效性。
Practical time‐varying formation cooperative control for high‐order nonlinear multi‐agent systems avoiding spatial resource conflict via safety constraints
The operation of multi‐agent systems (MAS) in space necessitates considerations for obstacle avoidance, collision prevention, and connectivity among agents. This coupling conflict, stemming from spatial resource utilization, poses a significant and non‐negligible threat to the safe operation of MAS. This article proposes a consensus control scheme for the time‐varying formation of MAS, incorporating functions for maintaining connectivity, collision avoidance, and obstacle dodging. This scheme effectively constrains the time‐varying formation tracking error within an arbitrarily small range. The considered system model takes a high‐order nonlinear form, with uncertainties and disturbances present in each order. This grants the control scheme with high generality and practicability. By employing barrier Lyapunov function to delineate the safe operational space of MAS, conflicts in spatial resource utilization are avoided. This approach simultaneously fulfills the requirements for connectivity maintenance, collision avoidance, and obstacle dodging in the safe operation of MAS. An additional rotation operator is integrated into the controller to smoothly address the “minima” problem, eliminating the need for external intervention. Gaussian radial basis function is used to estimate the nonlinear terms, uncertainties, and unknown perturbation online in the system. The stability of the MAS under the proposed control scheme is analyzed through Lyapunov function. Finally, numerical simulation results are demonstrated to explain the effectiveness of the control scheme.
期刊介绍:
Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.