{"title":"基于RBF神经网络的超跳混沌系统自适应滑模同步","authors":"Baojie Zhang","doi":"10.1109/ICICIP53388.2021.9642190","DOIUrl":null,"url":null,"abstract":"In this paper, we consider the synchronization of hyperjerk chaotic systems with different structures. Besides the order, the systems are unknown with external disturbances. We use sliding mode control method to deal with the external disturbances. Radial basis function (RBF) neural network is proposed to approximate the unknown system. Based on RBF neural network, adaptive sliding mode synchronization of different hyperjerk chaotic systems are introduced. Numerical results show the effectiveness of the synchronization scheme.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"274 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Sliding Mode Synchronization of Different Hyperjerk Chaotic Systems Using RBF Neural Network\",\"authors\":\"Baojie Zhang\",\"doi\":\"10.1109/ICICIP53388.2021.9642190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we consider the synchronization of hyperjerk chaotic systems with different structures. Besides the order, the systems are unknown with external disturbances. We use sliding mode control method to deal with the external disturbances. Radial basis function (RBF) neural network is proposed to approximate the unknown system. Based on RBF neural network, adaptive sliding mode synchronization of different hyperjerk chaotic systems are introduced. Numerical results show the effectiveness of the synchronization scheme.\",\"PeriodicalId\":435799,\"journal\":{\"name\":\"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)\",\"volume\":\"274 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICIP53388.2021.9642190\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP53388.2021.9642190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Sliding Mode Synchronization of Different Hyperjerk Chaotic Systems Using RBF Neural Network
In this paper, we consider the synchronization of hyperjerk chaotic systems with different structures. Besides the order, the systems are unknown with external disturbances. We use sliding mode control method to deal with the external disturbances. Radial basis function (RBF) neural network is proposed to approximate the unknown system. Based on RBF neural network, adaptive sliding mode synchronization of different hyperjerk chaotic systems are introduced. Numerical results show the effectiveness of the synchronization scheme.
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