首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Zonotopic set-membership state estimation for switched systems
Institution:1. CRIStAL, UMR CNRS 9189, Centrale Lille Institut, Villeneuve dAscq, France;2. Institut de Robòtica i Informàtica Industrial (CSIC-UPC) Carrer Llorens Artigas, 4-6, 08028 Barcelona;3. IBISC Laboratory, Univ Evry, Paris-Saclay University, Evry, France;1. Departamento de Automação e Sistemas, Universidade Federal de Santa Catarina, Florianópolis, Brazil;2. Université Grenoble Alpes, CNRS, Grenoble INP (Institute of Engineering, Univ. Grenoble Alpes), GIPSA-Lab, Grenoble 38000, France;3. Université de Lorraine, CNRS, CRAN, Nancy F-54000, France;1. Northwestern Polytechnical University, School of Automation, 1 Dongxianglu, Xi''an 710129, China;2. Key Lab of Information Fusion Technology (Ministry of Education);1. School of Chemical and Environmental Engineering, Liaoning University of Technology, Jinzhou, Liaoning, 121001, China;2. College of Science, Liaoning University of Technology, Jinzhou, Liaoning, 121001, China;1. Department of Aerospace Engineering, Sharif University of Technology, Tehran, Iran;2. Dipartimento di Elettronica Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy;1. German Jordanian University, School of Electrical Engineering and Information Technology, Amman Madaba Street, PO Box 35247, Amman 11180 Jordan;2. German Jordanian University, School of Basic Sciences and Humanities, Amman Madaba Street, PO Box 35247, Amman 11180 Jordan
Abstract:This paper proposes a new approach for set-membership state estimation of switched discrete-time linear systems subject to bounded disturbances and noises. A zonotopic outer approximation of the state estimation domain is computed and a new criterion is proposed to reduce the size of the zonotope at each sample time. The zonotopic set-membership estimator design for switched systems is provided within the LMI framework. The extension of the proposed scheme to deal with unknown inputs is also presented. An application to vehicle lateral dynamics state estimation is provided. Simulation results demonstrate the effectiveness of the proposed algorithm and highlight its advantages over the existing methods.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号