{"title":"An adaptive bearing rigid formation control of multi-agent systems with nonlinear dead-zone inputs","authors":"Qin Wang, Zitao Chen, Yang Yi, Qingcheng Shen","doi":"10.1177/00202940231214316","DOIUrl":null,"url":null,"abstract":"In this paper, an adaptive bearing rigid formation control strategy for a class of nonlinear system with unknown dead-zone inputs and external disturbance is proposed. Firstly, the I-Type fuzzy system is used to approximate the unknown nonlinear dynamics of the formation model, and the approximation errors and unknown external disturbance are eliminated by the parameter adaptive estimation. Furthermore, the adaptive dynamic estimation algorithm is utilized to estimate and compensate the unknown dead-zone parameters, effectively suppressing the impact of dead-zone on formation system performance. Finally, the stability of the formation system is proved based on LaSalle’s invariance principle, and the effectiveness of the algorithm is verified by simulation results.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"41 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/00202940231214316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, an adaptive bearing rigid formation control strategy for a class of nonlinear system with unknown dead-zone inputs and external disturbance is proposed. Firstly, the I-Type fuzzy system is used to approximate the unknown nonlinear dynamics of the formation model, and the approximation errors and unknown external disturbance are eliminated by the parameter adaptive estimation. Furthermore, the adaptive dynamic estimation algorithm is utilized to estimate and compensate the unknown dead-zone parameters, effectively suppressing the impact of dead-zone on formation system performance. Finally, the stability of the formation system is proved based on LaSalle’s invariance principle, and the effectiveness of the algorithm is verified by simulation results.
本文针对一类具有未知死区输入和外部扰动的非线性系统,提出了一种自适应轴承刚性编队控制策略。首先,利用 I 型模糊系统对编队模型的未知非线性动力学进行近似,并通过参数自适应估计消除近似误差和未知外部扰动。此外,利用自适应动态估计算法对未知死区参数进行估计和补偿,有效抑制了死区对编队系统性能的影响。最后,根据拉萨尔不变性原理证明了编队系统的稳定性,并通过仿真结果验证了算法的有效性。