NDLI: Distributed estimation for stochastic hybrid systems with event-triggered sensor schedule

Content Provider	IET Digital Library
Author	Zhang, Cui Jia, Yingmin
Abstract	This study deals with the state estimation problem for stochastic hybrid systems with event-triggered sensor schedule. By employing the basic interacting multiple model (IMM) approach, a novel event-triggered state estimator has been proposed for stochastic hybrid systems based on a closed-loop schedule rule. To compute the mode probabilities in the IMM estimator, a set of sigma points are generated to produce the pseudo-measurements when the sensor measurements are unavailable. Then, the event-triggered state estimator is extended to develop a distributed estimator in the sense of linear minimum mean square error, where the fused estimates are used to implement the re-initialisation in the interacting stage of the IMM estimator. The performance of proposed estimators is illustrated through the Monte Carlo simulations involving tracking a manoeuvring target in the two-dimensional experiment. Simulation results show that the performance of the proposed estimator is compared with that of the existing filter with a reduced computational burden.
Starting Page	173
Ending Page	181
Page Count	9
ISSN	17518644
Volume Number	11
e-ISSN	17518652
Issue Number	Issue 2, Jan (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/11/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2015.1300
Journal	IET Control Theory & Applications
Publisher Date	2016-10-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Closed Loop System Closed-loop Schedule Rule Event-triggered Sensor Schedule Event-triggered State Estimator IMM Approach Interacting Multiple Model Interpolation And Function Approximation Least Mean Squares Method Linear Minimum Mean Square Error Manoeuvring Target Tracking Monte Carlo Method Monte Carlo Simulation Method Numerical Analysis Sensor Sensor Measurement Stochastic Hybrid System Stochastic System Time Varying Control System Transducers And Sensing Device
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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