{"title":"Cooperative source seeking via gradient estimation and formation control (Part 1)","authors":"Esteban Rosero, H. Werner","doi":"10.1109/CONTROL.2014.6915212","DOIUrl":null,"url":null,"abstract":"In this paper and its companion paper [14], the problem of cooperative source seeking by a formation of mobile agents is considered. Each agent is equipped with position and signal strength measurement sensors; their task is to find the maximum of the scalar field. Agents exchange information with neighboring agents through a communication network. In the first part of this couple of papers, a distributed gradient estimation for each agent and a decentralized navigation controller for single- and double-integrator models are presented. When the signal measurements are corrupted by noise, distributed consensus filters are used in order to estimate the gradient direction. The strategy is based on both a gradient estimating algorithm and a formation controller. Stability conditions are provided. Numerical simulations illustrate the effectiveness of the proposed control law. Part two extends this approach to general linear time-invariant models.","PeriodicalId":269044,"journal":{"name":"2014 UKACC International Conference on Control (CONTROL)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 UKACC International Conference on Control (CONTROL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONTROL.2014.6915212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
In this paper and its companion paper [14], the problem of cooperative source seeking by a formation of mobile agents is considered. Each agent is equipped with position and signal strength measurement sensors; their task is to find the maximum of the scalar field. Agents exchange information with neighboring agents through a communication network. In the first part of this couple of papers, a distributed gradient estimation for each agent and a decentralized navigation controller for single- and double-integrator models are presented. When the signal measurements are corrupted by noise, distributed consensus filters are used in order to estimate the gradient direction. The strategy is based on both a gradient estimating algorithm and a formation controller. Stability conditions are provided. Numerical simulations illustrate the effectiveness of the proposed control law. Part two extends this approach to general linear time-invariant models.