{"title":"Adaptive hierarchical control for a class of MIMO uncertain underactuated systems","authors":"A. Kulkarni, A. Kumar","doi":"10.1109/ICCIC.2014.7238353","DOIUrl":null,"url":null,"abstract":"This paper presents an adaptive control strategy which combines the hierarchical control scheme with adaptive wavelet neural network for a class of multi-input multi-output (MIMO) underactuated systems with uncertain dynamics. Proposed scheme develops a systematic framework of the control components by applying hierarchical scheme to underactuated system. Wavelet neural networks are used to mimic the system uncertainties. Adaptive parameters of the wavelet network are tuned on line using gradient based approach. Uniformly ultimately bounded (UUB) stability of the closed loop system is analyzed in the sense of Lyapunov theory. Simulation results demonstrate the performance of proposed control scheme.","PeriodicalId":187874,"journal":{"name":"2014 IEEE International Conference on Computational Intelligence and Computing Research","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Computational Intelligence and Computing Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIC.2014.7238353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents an adaptive control strategy which combines the hierarchical control scheme with adaptive wavelet neural network for a class of multi-input multi-output (MIMO) underactuated systems with uncertain dynamics. Proposed scheme develops a systematic framework of the control components by applying hierarchical scheme to underactuated system. Wavelet neural networks are used to mimic the system uncertainties. Adaptive parameters of the wavelet network are tuned on line using gradient based approach. Uniformly ultimately bounded (UUB) stability of the closed loop system is analyzed in the sense of Lyapunov theory. Simulation results demonstrate the performance of proposed control scheme.