UKF based Fault Detection and State Estimation for Nonlinear Systems with Correlated Noise
作者单位：Key Laboratory of Intelligent Control and Decision of Complex SystemsSchool of AutomationBeijing Institute of Technology School of Information and Communication EngineeringBeijing University of Posts and Telecommunications
会议名称：《第36届中国控制会议》
主办单位：Dalian University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
会议日期：2017年
学科分类：080902[工学-电路与系统] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学]
基 金：supported by the NSFC under grant No. 61603365 and 61473040 the Beijing Natural Science Foundation under grant No.4161001 the innovative research groups of the national nature science foundation of China under grant 61321002
关 键 词：fault detection state estimation correlated noise nonlinear system
摘 要：State estimation and fault diagnosis are essential topics for dynamic *** Kalman fllter（UKF） has been widely applied in nonlinear *** classical UKF algorithm is built on the premise that process noise and measurement noise is *** practical problems,this assumption is not always *** addition,due to the limitation of communication and sensor fault,etc.,data missing or unreliable measurements will happen ***,it is very important to study the state estimation of nonlinear systems with unreliable measurements and correlated *** this paper,an UKF based state estimation algorithm with unreliable observations under correlated noise is presented.A numerical example is given to show the feasibility and effectiveness of the presented algorithm.