Variance-constrained robust estimation for uncertain systems with multiple packet dropouts

2011 ◽  
Vol 34 (1) ◽  
pp. 53-68 ◽  
Author(s):  
Baofeng Wang ◽  
Ge Guo ◽  
Wei Yue
Keyword(s):  
Robust Estimation ◽  
Uncertain Systems ◽  
Packet Dropouts

scholarly journals Modelling and Estimation for Uncertain Systems with Transmission Delays, Packet Dropouts, and Out-of-Order Packets

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Li Liu ◽  
Aolei Yang ◽  
Wenju Zhou ◽  
Wasif Naeem ◽  
Gang Wang ◽  
...  
Keyword(s):  
Uncertain Systems ◽  
Estimation Accuracy ◽  
Delay Compensation ◽  
Packet Dropouts ◽  
Transmission Delays ◽  
Cross Covariance ◽  
Linear Delay ◽  
Optimal Linear ◽  
Estimation Scheme ◽  
Distributed Measurement

The study focuses on the modelling and estimation of a class of discrete-time uncertain systems, including network-induced random delays, packet dropouts, and out-of-order packets during the data transmission from the plant to the estimator. In order to improve system performance, event-triggered signal selection method is used to establish the system model. Based on this model, a distributed measurement and centralized fusion estimation scheme is designed using a robust finite horizon Kalman-type filter. Since the phenomena caused by the network-induced deteriorate estimation accuracy, a time-based reorganization measurement is employed to design a linear delay compensation strategy based on estimation. Moreover, in order to obtain the optimal linear estimation, weighted fusion estimation approach is used to perform information collaboration through the error cross-covariance matrix. Simulation results demonstrate that the proposed method has higher estimation performance than the existing methods in this study.

Robust Estimation for Discrete-Time Uncertain Systems with Markov Jump Delays

2014 ◽  
Vol 945-949 ◽  
pp. 2646-2650
Author(s):  
Lin Ping Feng ◽  
Shuang Pan ◽  
Feng Xiao
Keyword(s):  
Least Squares ◽  
Robust Estimation ◽  
Discrete Time ◽  
Uncertain Systems ◽  
Uncertain System ◽  
Markov Jump ◽  
Regularized Least Squares ◽  
Random Delays

This paper is concerned with the dynamic Markov jump filters for discrete-time uncertain system with random delays in the observations. By applying the measurement reorganization approach, the system is further transformed into the delay-free one with Markov jump parameters. Then the estimator is derived by using the regularized least-squares and Markov jump filter theories. At last, a simulation example is given to illustrate the effectiveness of the proposed result.

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