{"title":"利用状态反馈和基于扩展卡尔曼滤波器的控制方案实现一类有不确定性和无不确定性非线性系统的同步化","authors":"R. K. Ranjan, Bharat Bhushan Sharma","doi":"10.1115/1.4064270","DOIUrl":null,"url":null,"abstract":"\n The paper elaborates on various synchronization aspects for nonlinear systems belonging to a specific class, under different scenarios. The method proposed in the article refers to the Lyapunov direct method and Extended Kalman Filter technique to ensure the convergence of the slave state trajectories to the corresponding master state trajectories. Initially, an output feedback-based synchronization approach is attempted, assuming that bounds of unmeasurable states are available for controller synthesis. However, this approach has limitations in handling complete parametric uncertainty for the considered class of systems. To overcome this limitation, a state feedback-based synchronization scheme is presented, and an appropriate state feedback controller and parametric adaptation laws are designed analytically. In the case where only output states are accessible for feedback, and the system is subjected to complete parametric uncertainty, an Extended Kalman Filter based estimation scheme is used. This approach facilitates achieving synchronization despite the presence of external channel noise disturbances with a Gaussian distribution. The potency of the proposed results is successfully substantiated for the chaotic Lorenz system, which belongs to the considered class of nonlinear systems. Ultimately, numerical simulations are provided to corroborate the efficacy of proposed synchronization and estimation strategy.","PeriodicalId":54858,"journal":{"name":"Journal of Computational and Nonlinear Dynamics","volume":"49 30","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Synchronization of a Class of Nonlinear Systems With and Without Uncertainty Using State Feedback and Extended Kalman Filter Based Control Scheme\",\"authors\":\"R. K. Ranjan, Bharat Bhushan Sharma\",\"doi\":\"10.1115/1.4064270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The paper elaborates on various synchronization aspects for nonlinear systems belonging to a specific class, under different scenarios. The method proposed in the article refers to the Lyapunov direct method and Extended Kalman Filter technique to ensure the convergence of the slave state trajectories to the corresponding master state trajectories. Initially, an output feedback-based synchronization approach is attempted, assuming that bounds of unmeasurable states are available for controller synthesis. However, this approach has limitations in handling complete parametric uncertainty for the considered class of systems. To overcome this limitation, a state feedback-based synchronization scheme is presented, and an appropriate state feedback controller and parametric adaptation laws are designed analytically. In the case where only output states are accessible for feedback, and the system is subjected to complete parametric uncertainty, an Extended Kalman Filter based estimation scheme is used. This approach facilitates achieving synchronization despite the presence of external channel noise disturbances with a Gaussian distribution. The potency of the proposed results is successfully substantiated for the chaotic Lorenz system, which belongs to the considered class of nonlinear systems. Ultimately, numerical simulations are provided to corroborate the efficacy of proposed synchronization and estimation strategy.\",\"PeriodicalId\":54858,\"journal\":{\"name\":\"Journal of Computational and Nonlinear Dynamics\",\"volume\":\"49 30\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational and Nonlinear Dynamics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4064270\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Nonlinear Dynamics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4064270","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Synchronization of a Class of Nonlinear Systems With and Without Uncertainty Using State Feedback and Extended Kalman Filter Based Control Scheme
The paper elaborates on various synchronization aspects for nonlinear systems belonging to a specific class, under different scenarios. The method proposed in the article refers to the Lyapunov direct method and Extended Kalman Filter technique to ensure the convergence of the slave state trajectories to the corresponding master state trajectories. Initially, an output feedback-based synchronization approach is attempted, assuming that bounds of unmeasurable states are available for controller synthesis. However, this approach has limitations in handling complete parametric uncertainty for the considered class of systems. To overcome this limitation, a state feedback-based synchronization scheme is presented, and an appropriate state feedback controller and parametric adaptation laws are designed analytically. In the case where only output states are accessible for feedback, and the system is subjected to complete parametric uncertainty, an Extended Kalman Filter based estimation scheme is used. This approach facilitates achieving synchronization despite the presence of external channel noise disturbances with a Gaussian distribution. The potency of the proposed results is successfully substantiated for the chaotic Lorenz system, which belongs to the considered class of nonlinear systems. Ultimately, numerical simulations are provided to corroborate the efficacy of proposed synchronization and estimation strategy.
期刊介绍:
The purpose of the Journal of Computational and Nonlinear Dynamics is to provide a medium for rapid dissemination of original research results in theoretical as well as applied computational and nonlinear dynamics. The journal serves as a forum for the exchange of new ideas and applications in computational, rigid and flexible multi-body system dynamics and all aspects (analytical, numerical, and experimental) of dynamics associated with nonlinear systems. The broad scope of the journal encompasses all computational and nonlinear problems occurring in aeronautical, biological, electrical, mechanical, physical, and structural systems.