{"title":"Fully Distributed Target Encircling Control of Autonomous Surface Vehicles Based on Noncooperative Games","authors":"Yue Jiang;Zhongkui Li","doi":"10.1109/TIV.2024.3372652","DOIUrl":null,"url":null,"abstract":"This paper addresses cooperative target encircling of multiple autonomous surface vehicles (ASVs) with private and potentially competitive objectives. A fully distributed encircling control approach is proposed based on noncooperative games. Specifically, a fully distributed estimator with an adaptive gain is developed to estimate the target information without using global state or topology knowledge. Based on a low-frequency learning technique, a fuzzy predictor is presented to approximate the unknown vehicle kinematics induced by uncertain nonlinearities and environmental disturbances. By decoupling the cooperative target encircling into an encircling task and a spacing task, an encircling control law and a spacing control law are designed based on fully distributed Nash equilibrium seeking for achieving the private control objective of each ASV. The input-to-state stability of the closed-loop system is proven via cascade analysis. Simulation results are provided to illustrate the effectiveness of the noncooperative game-based control method for ASVs in circumnavigation missions.","PeriodicalId":36532,"journal":{"name":"IEEE Transactions on Intelligent Vehicles","volume":"9 4","pages":"4769-4779"},"PeriodicalIF":14.0000,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Intelligent Vehicles","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10458361/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper addresses cooperative target encircling of multiple autonomous surface vehicles (ASVs) with private and potentially competitive objectives. A fully distributed encircling control approach is proposed based on noncooperative games. Specifically, a fully distributed estimator with an adaptive gain is developed to estimate the target information without using global state or topology knowledge. Based on a low-frequency learning technique, a fuzzy predictor is presented to approximate the unknown vehicle kinematics induced by uncertain nonlinearities and environmental disturbances. By decoupling the cooperative target encircling into an encircling task and a spacing task, an encircling control law and a spacing control law are designed based on fully distributed Nash equilibrium seeking for achieving the private control objective of each ASV. The input-to-state stability of the closed-loop system is proven via cascade analysis. Simulation results are provided to illustrate the effectiveness of the noncooperative game-based control method for ASVs in circumnavigation missions.
本文论述了多个自主水面飞行器(ASV)合作包围目标的问题,这些飞行器具有私人目标和潜在竞争目标。本文提出了一种基于非合作博弈的全分布式包围控制方法。具体来说,开发了一种具有自适应增益的全分布式估计器,以在不使用全局状态或拓扑知识的情况下估计目标信息。在低频学习技术的基础上,提出了一种模糊预测器,用于近似由不确定非线性和环境干扰引起的未知车辆运动学。通过将合作目标包围解耦为包围任务和间隔任务,设计了基于全分布纳什均衡寻求的包围控制法则和间隔控制法则,以实现每个 ASV 的私有控制目标。通过级联分析证明了闭环系统的输入到状态稳定性。仿真结果说明了基于非合作博弈的控制方法在 ASV 环绕飞行任务中的有效性。
期刊介绍:
The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges.
Our focus is on providing critical information to the intelligent vehicle community, serving as a dissemination vehicle for IEEE ITS Society members and others interested in learning about the state-of-the-art developments and progress in research and applications related to intelligent vehicles. Join us in advancing knowledge and innovation in this dynamic field.