Search results for: Zili Deng

Items from 1 to 20 out of 100 results

article

Robust weighted state fusion Kalman estimators for networked systems with mixed uncertainties

Chunshan Yang, Zhibo Yang, Zili Deng

Information Fusion > 2019 > 45 > C > 246-265

This paper is concerned with robust weighted state fusion estimation problem for a class of time-varying multisensor networked systems with mixed uncertainties including uncertain-variance multiplicative and linearly correlated additive white noises, and packet dropouts. By augmented state method and fictitious noise technique, the original system is converted into one with only uncertain noise variances...

article

Robust Kalman estimators for systems with mixed uncertainties

Wenqiang Liu, Xuemei Wang, Zili Deng

Optimal Control Applications and Methods > 39 > 2 > 735 - 756

This paper addresses the problem of designing robust Kalman estimators for uncertain systems with mixed uncertainties including the same uncertain‐variance multiplicative noise in state and measurement matrices, missing measurements, and uncertain‐variance linearly correlated measurement and process white noise. By introducing fictitious noise to compensate for multiplicative noise, the system under...

article

Robust Kalman estimators for systems with multiplicative and uncertain-variance linearly correlated additive white noises

Wenqiang Liu, Xuemei Wang, Zili Deng

Aerospace Science and Technology > 2018 > 72 > C > 230-247

For linear discrete-time stochastic systems with mixed uncertainties including multiplicative and uncertain-variance linearly correlated additive white noises, this paper addresses the problem of designing robust Kalman estimators. By the fictitious noise-based Lyapunov equation approach, the system under consideration is converted into one with only uncertain noise variances. Based on the worst-case...

article

Robust weighted fusion Kalman estimators for systems with multiplicative noises, missing measurements and uncertain-variance linearly correlated white noises

Xuemei Wang, Wenqiang Liu, Zili Deng

Aerospace Science and Technology > 2017 > 68 > C > 331-344

For linear discrete time-varying and time-invariant multisensor uncertain systems with multiplicative noises, missing measurements and uncertain-variance linearly correlated white noises, by introducing the fictitious noises to compensate the stochastic uncertainties, the system under consideration can be converted into one with only uncertain noise variances. According to the minimax robust estimation...

article

Robust weighted fusion Kalman estimators for multi-model multisensor systems with uncertain-variance multiplicative and linearly correlated additive white noises

Xuemei Wang, Wenqiang Liu, Zili Deng

Signal Processing > 2017 > 137 > C > 339-355

For multi-model multisensor systems with both the uncertain-variance multiplicative and linearly correlated additive white noises, a universal fictitious noise-based Lyapunov equation approach is presented, by which the original system can be converted into one with only uncertain additive noise variances, and then the local and four weighted fused minimax robust time-varying Kalman estimators (predictor,...

chapter

Robust white noise deconvolution estimators for systems with uncertain-variance linearly correlated white noises and missing measurements

Wenqiang Liu, Zili Deng

2017 36th Chinese Control Conference (CCC) > 5070 - 5077

2017 36th Chinese Control Conference (CCC)

Estimating input signal of a system is called deconvolution or input estimation. The white noise deconvolution has important applications in oil seismic exploration, communications, and signal processing. This paper addresses the problem of designing robust white noise deconvolution estimators for a class of uncertain systems with missing measurements, uncertain noise variances and linearly correlated...

chapter

Robust weighted fusion Kalman estimators for systems with uncertain-variance multiplicative and additive noises and missing measurements

Zili Deng, Zhibo Yang

2017 20th International Conference on Information Fusion (Fusion) > 1 - 8

2017 20th International Conference on Information Fusion (Fusion)

This paper investigates the robust weighted fusion estimation problem of multi-sensor systems with mixed uncertainties, including stochastic parameter uncertainties, missing measurements and uncertain noise variances. The stochastic parameter uncertainties are described by multiplicative noise. Especially, the variances of both the multiplicative and additive noises are uncertain. By introducing two...

chapter

Robust weighted fusion white noise deconvolution estimators with uncertain-variance linearly correlated white noises and missing measurements

Wenqiang Liu, Zili Deng

2017 20th International Conference on Information Fusion (Fusion) > 1 - 8

2017 20th International Conference on Information Fusion (Fusion)

This paper addresses the design problem of robust weighted fusion white noise deconvolution estimators for a class of uncertain multisensor systems with missing measurements, uncertain noise variances and linearly correlated white noises. By introducing the fictitious noise, the considered system is converted into one with only uncertain noise variances. According to the minimax robust estimation...

chapter

Multi-model robust weighted fusion steady-state Kalman estimators for systems with uncertain-variance multiplicative and additive white noises

Xuemei Wang, Zili Deng

2017 20th International Conference on Information Fusion (Fusion) > 1 - 8

2017 20th International Conference on Information Fusion (Fusion)

For multi-model multisensor systems with uncertain-covariance multiplicative and additive white noises, a universal fictitious noise-based Lyapunov equation approach is presented, by which the original system can be converted into one with only uncertain additive noise variances. According to the minimax robust estimation principle, based on the worst-case system with conservative upper bounds of...

chapter

Information fusion robust guaranteed cost Kalman predictors for systems with multiplicative noises and uncertain noise variances

Chunshan Yang, Zili Deng

2017 20th International Conference on Information Fusion (Fusion) > 1 - 8

2017 20th International Conference on Information Fusion (Fusion)

This paper is concerned with the guaranteed cost robust weighted fusion prediction problem for discrete-time systems with multiplicative noises, colored measurements noises and uncertain noise variances. Applying the augmented state approach and a fictitious noise technique, the original system is converted into a system only with uncertain noise variances. Two classes of guaranteed cost robust weighted...

chapter

Multi-model robust weighted fusion steady-state Kalman estimators with uncertain-covariance linearly correlated white noises

Xuemei Wang, Zili Deng

2017 29th Chinese Control And Decision Conference (CCDC) > 4873 - 4879

2017 29th Chinese Control And Decision Conference (CCDC)

For multi-model multisensor systems with uncertain covariance linearly correlated white noises, the design problems of the robust weighted fusion steady-state Kalman estimators (predictor, filter, smoother) are addressed. According to the minimax robust estimation principle, applying Lyapunov equation approach, a unified direct design approach to obtain the local and three weighted fusion robust steady-state...

chapter

Robust weighted fusion Kalman predictor for multisensor systems with multiplicative noises and uncertain noise variances

Wenqiang Liu, Zili Deng

2017 29th Chinese Control And Decision Conference (CCDC) > 3812 - 3817

2017 29th Chinese Control And Decision Conference (CCDC)

This paper addresses the design of robust weighted fusion Kalman predictor for a class of linear discrete-time multisensor systems with multiplicative noises in the state and measurement matrices, and with the uncertain noise variances. By introducing two fictitious noises, the considered system is converted into one with only uncertain noise variances. According to the minimax robust estimation principle,...

chapter

Robust measurement fusion Kalman predictors for systems with uncertain-variance multiplicative and additive noises

Zhibo Yang, Chenjian Ran, Zili Deng

2017 29th Chinese Control And Decision Conference (CCDC) > 425 - 431

2017 29th Chinese Control And Decision Conference (CCDC)

In this paper, the robust measurement fusion prediction problem for multi-sensor systems with stochastic parameter uncertainties in state equation and uncertain noise variances are investigated, where the stochastic parameters uncertainties are described by multiplicative noises. Especially, both the multiplicative and the additive noise variances are uncertain. By introducing the fictitious noise,...

article

Robust centralized and weighted measurement fusion Kalman estimators for multisensor systems with multiplicative and uncertain-covariance linearly correlated white noises

Wenqiang Liu, Xuemei Wang, Zili Deng

Journal of the Franklin Institute > 2017 > 354 > 4 > 1992-2031

This paper addresses the design of robust centralized and weighted measurement fusion (WMF) Kalman estimators for a class of uncertain multisensor systems with linearly correlated measurement and process white noises. The uncertainties of the systems include the same multiplicative noises in state and measurement matrices, and the uncertain noise variances. By introducing the fictitious noises to...

chapter

Robust centralized and weighted measurement fusion steady-state Kalman estimators with uncertain linearly correlated white noises

Xuemei Wang, Zili Deng

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT) > 290 - 297

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

For the multisensor systems with uncertain-variance linearly correlated white noises, according to the minimax robust estimation principle, applying the weighted least squares(WLS) and the full-rank decomposition of matrix, the robust centralized fusion and weighted measurement fusion steady-state Kalman estimators (filter, predictor and smoother) are presented in a unified framework. Their equivalence...

chapter

Robust weighted fusion Kalman estimators for ARMA signals with uncertain noise variances and missing measurements

Zhibo Yang, Zili Deng

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT) > 280 - 285

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

The design problem of robust fusion Kalman estimators (predictor, filter, smoother) for multi-sensor multichannel autoregressive moving average (ARMA) signal system with uncertain noise variances and missing measurements is addressed. Applying the augmented state-space method and introducing fictitious noises, the ARMA signal system with missing measurements and uncertain noise variances is converted...

chapter

Robust weighted fusion Kalman filter with multiplicative noises, uncertain noise variances, and missing measurements

Wenqiang Liu, Zili Deng

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT) > 255 - 261

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

In this work, the robust weighted state fusion Kalman filter is studied for multisensor systems with multiplicative noises, uncertain noise variances and missing measurements. By introducing two fictitious noises, the system is converted into one with only uncertain noise variances. According to the minimax robust estimation principle, based on the worst-case conservative system with the upper bound...

chapter

Robust guaranteed cost measurement fusion steady-state Kalman filters with uncertain noise variances

Chunshan Yang, Zili Deng

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT) > 249 - 254

2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

In this work, guaranteed cost robust centralized fusion (CF) and weighted measurement fusion (WMF) steady-state Kalman filters problems in multisensor system with uncertain noise variances are addressed. By parameterzing the perturbations of uncertain noise variances, two classes of guaranteed cost robust CF and WMF Kalman filters are proposed based on minimax robust estimation principle (MREP). The...

article

Guaranteed Cost Robust Weighted Measurement Fusion Kalman Estimators With Uncertain Noise Variances and Missing Measurements

Chunshan Yang, Zili Deng

IEEE Sensors Journal > 2016 > 16 > 14 > 5817 - 5825

This paper is concerned with a guaranteed cost robust weighted measurement fusion (WMF) estimation problem for a multisensor system with both uncertain noise variances and missing measurements. By introducing the fictitious measurement white noises, the original multisensor system is converted into one only with uncertain noise variances. Two classes of guaranteed cost robust WMF Kalman estimators...

chapter

Robust measurement fusion Kalman filter for multisensor systems with multiplicative noises and uncertain noise variances

Wenqiang Liu, Xuemei Wang, Zili Deng

2016 12th World Congress on Intelligent Control and Automation (WCICA) > 3180 - 3186

2016 12th World Congress on Intelligent Control and Automation (WCICA)

This paper addresses the design of robust measurement fusion Kalman filter for linear discrete-time multisensor systems with multiplicative noises perturbations both on state equation and measurement equations, and with uncertain noise variances. By introducing two fictitious noises, the system is converted into one with only uncertain noise variances. According to the minimax robust estimation principle,...

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INFONA - science communication portal

Search results for: Zili Deng

Robust weighted state fusion Kalman estimators for networked systems with mixed uncertainties

Robust Kalman estimators for systems with mixed uncertainties

Robust Kalman estimators for systems with multiplicative and uncertain-variance linearly correlated additive white noises

Robust weighted fusion Kalman estimators for systems with multiplicative noises, missing measurements and uncertain-variance linearly correlated white noises

Robust weighted fusion Kalman estimators for multi-model multisensor systems with uncertain-variance multiplicative and linearly correlated additive white noises

Robust white noise deconvolution estimators for systems with uncertain-variance linearly correlated white noises and missing measurements

Robust weighted fusion Kalman estimators for systems with uncertain-variance multiplicative and additive noises and missing measurements

Robust weighted fusion white noise deconvolution estimators with uncertain-variance linearly correlated white noises and missing measurements

Multi-model robust weighted fusion steady-state Kalman estimators for systems with uncertain-variance multiplicative and additive white noises

Information fusion robust guaranteed cost Kalman predictors for systems with multiplicative noises and uncertain noise variances

Multi-model robust weighted fusion steady-state Kalman estimators with uncertain-covariance linearly correlated white noises

Robust weighted fusion Kalman predictor for multisensor systems with multiplicative noises and uncertain noise variances

Robust measurement fusion Kalman predictors for systems with uncertain-variance multiplicative and additive noises

Robust centralized and weighted measurement fusion Kalman estimators for multisensor systems with multiplicative and uncertain-covariance linearly correlated white noises

Robust centralized and weighted measurement fusion steady-state Kalman estimators with uncertain linearly correlated white noises

Robust weighted fusion Kalman estimators for ARMA signals with uncertain noise variances and missing measurements

Robust weighted fusion Kalman filter with multiplicative noises, uncertain noise variances, and missing measurements

Robust guaranteed cost measurement fusion steady-state Kalman filters with uncertain noise variances

Guaranteed Cost Robust Weighted Measurement Fusion Kalman Estimators With Uncertain Noise Variances and Missing Measurements

Robust measurement fusion Kalman filter for multisensor systems with multiplicative noises and uncertain noise variances

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