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Attitude sensor fault diagnosis based on Kalman filter of discrete-time descriptor system

Journal of systems Engineering and Electronics 2012年第6期23卷 914-920页

作者： ZhenhuaWang Yi Shen Xiaolei Zhang School of Astronautics Harbin Institute of Technology Harbin 150001 P. R. China

To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to esti-mate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method.

关键词： discrete-time descriptor system Kalman filter satel-lite attitude sensor fault estimation.

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维普期刊数据库

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Sensor Fault Diagnosis Observer Design for Linear Sampled-Data descriptor system with Time-Vary Delay

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Journal of Harbin Institute of Technology(New Series) 2019年第6期26卷 8-18页

作者： Mao Wang Tiantian Liang Zhenhua Zhou Space Control and Inertial Technology Research Center Harbin Institute of TechnologyHarbin 150001China Changzhou Vocational Institute of Light Industry Technology Changzhou 213000JiangsuChina

In this paper, a robust sensor fault diagnosis observer with non-singular structure is proposed for a class of linear sampled-data descriptor system with state time-vary delay. Firstly, a sampled-data descriptor model with time-vary delay is proposed and transformed into a discrete-time non-singular one. Then, a robust sensor fault diagnosis observer is proposed based on the state estimation error and the measurement residual, this observer can guarantee the robustness of the residual against the augmented disturbance and the sensor fault, which means the H∞ performance index is satisfied. As the confining matrix of the designed observer parameters does not meet the Linear Matrix Inequality (LMI), a cone complementary linearization (CCL) algorithm is proposed to solve this problem. The decision logic of the residual is obtained by the residual evaluation function. Simulation results show the effectiveness of the method.

关键词： descriptor system sampled-data system time-vary delay sensor fault diagnosis observer design

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Self-tuning Reduced-order Kalman Smoother for the descriptor system

Self-tuning Reduced-order Kalman Smoother for the Descriptor...

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第30届中国控制与决策会议

作者： Chengxiang Liu Chenjian Ran Department of Automation Heilongjiang University

For the linear stochastic descriptor system with uncorrelated noises, the self-tuning reduced-order smoothing problem is solved, when the noise variances of the process noise and measurement noise are unknown. The consistent estimates of these unknown noise variances are obtained by applying the correlation method, and the optimal Kalman reduced-order smoother is obtained based on the singular value decomposition method and the classical Kalman filtering theory. Then substituting these consistent estimates of unknown noise variances into the optimal reduced-order Kalman smoother yields the self-tuning reduced-order smoother and the smoothing error variance. A example of singular system verifies the effectiveness.

关键词： descriptor system Unknown noise variances Singular value decomposition method Self-tuning smoother

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Robust H2 Control for descriptor system Based on New Bounded Real Lemma

Robust H2 Control for Descriptor System Based on New Bounded...

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第二十七届中国控制会议

作者： Lu Renquan1,Du Wei1,Xue Lin2 1.Institute of Information and Control,Hangzhou Dianzi University,Hangzhou 310018,P.R.China 2.Electromechanical Irrigation and Drainage Management Station Dongyang City,Dongyang 150001,P.R.China

This paper is concerned with the problem of robust H2 control for uncertain continuous descriptor system based on new bounded real *** purpose is to present sufficient and necessary conditions such that the uncertain descriptor system is regular,impulse free and stable for all admissible uncertainties,while the H2 norm of the descriptor system is less than a given positive numberγ.To this end,a new bounded real lemma for the robust H2 control problem is firstly derived in terms of a strict linear matrix inequality（LMI） .Secondly,based on this bounded real lemma,one method of designing a state feedback controller is developed to guarantee the robust H2 ***,a numerical example is provided to demonstrate the effectiveness of the proposed method.

关键词： descriptor system Robust H2 control Linear matrix inequality Norm-bounded uncertainties

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Robust centralized fusion Kalman predictor for uncertain multisensor descriptor system

Robust centralized fusion Kalman predictor for uncertain mul...

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第37届中国控制会议

作者： Guili Tao Wenqiang Liu Computer and Information Engineering College Heilongjiang University of Science and Technology

For multisensor descriptor discrete stochastic linear system with uncertain noise variances, using the matrix singular value decomposition, it is transformed into two reduced-order non-descriptor subsystems. The state predictor problem of original descriptor system is transformed into predictor problem of normal system. According to minimax robust estimation principle,based on the worst-case system with the conservative upper bounds of the noise variances, the robust local and centralized fusion steady-state Kalman predictors are presented. Using the Lyapunov equation approach, their robustness are proved. A simulation example shows correctness of the proposed algorithms.

关键词： Robust descriptor system Uncertain Noise Variances Lyapunov Equation Approach

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Robust steady-state Kalman filter for descriptor system with uncertain-variance noise and packet dropout

Robust steady-state Kalman filter for descriptor system with...

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第40届中国控制会议

作者： Wentao liu Chenjian Ran Yinfeng Dou Yuan Gao Hao Shen Electronic Engineering College Heilongjiang University

For the linear stochastic descriptor system with packet dropout and uncertain-variance noises, the robust steady-state filtering problem is addressed. Applying the singular value decomposition（SVD） approach, augmented state approach and the fictitious noise approach, the original descriptor system is transformed to new standard system only with uncertain-variance fictitious noises. Based on Kalman filtering and minimax robust estimation principle, the robust steady-state Kalman filter is presented by replacing the unrealization conservative measurement by the actual measurement in the conservative steady-state Kalman filter. Further, the robustness is proved by the Lyapunov equation approach, i.e., the actual filtering error variance is guaranteed to have minimal upper bounds for all admissible uncertainties. A simulation example about circuits system verifies the correctness and effectiveness of the proposed results.

关键词： descriptor system robust steady-state Kalman filter packet dropout uncertain-variance noises

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Stabilization of descriptor system with Uncertainties in the Derivative Coefficient Matrix

Stabilization of Descriptor System with Uncertainties in the...

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2010 Chinese Control and Decision Conference

作者： Yufa Teng~1,Mingxue Zhang~1,Fuhong Wang~1,Qingling Zhang~2,Jianzhong Hao~1 1.Xuzhou Air Force Academy,Xuzhou 221000 2.College of Science,Northeastern University,Shenyang,110004

＜正＞To the robust normalization and robust stabilization for the descriptor systems with uncertain parameters,the matrix inequations and Lyapunov ineqation are used to get,respectively,sufficient conditions for the normalization of closed-loop descriptor systems via proportional and derivative state feedback（PDSF） and proportional and derivative output feedback（PDOF）,a sufficient condition for the robust stabilization of uncertain descriptor systems via PDSF, and a sufficient condition for robust stabilization of the uncertain interconnected large-scale systems.A numerical example is given for the verification of the results.

关键词： descriptor system PDSF PDOF Robust normalization Robust stabilization

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T-S Fuzzy Design for Nonlinear State-Delayed descriptor system Via Sliding Mode Control

T-S Fuzzy Design for Nonlinear State-Delayed Descriptor Syst...

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第三十届中国控制会议

作者： HAN Chunsong~(1,3),ZHANG Guojiang~2,ZENG Qingshuang~1,WU Ligang~1 1.Space Control and Inertial Technology Research Center,Harbin Institute of Technology,Harbin 150001,P.R.China 2.Control and Simulation Research Center,Harbin Institute of Technology,Harbin 150001,P.R.China 3.School of Computer and Control Engineering,Qiqihar University,Qiqihar,161006,P.R.China

＜正＞This paper is concerned with the problem of sliding mode control（SMC） of a class of Takagi-Sugeno（T-S） fuzzy descriptor system with *** integral-type sliding surface function is designed by taking the descriptor matrix into account,thus the resulting sliding mode dynamics is a full-order uncertain T-S fuzzy descriptor time-delay *** use of the delay partitioning technique,a delay-dependent criterion is established,which ensures the sliding mode dynamics to be regular,impulse-free and ***,a SMC law is synthesized to guarantee the stability of the closed-loop system,and the proposed SMC law can drive the dynamics of controlled system into a designated sliding surface in a finite ***,a numerical example is provided to illustrate the effectiveness of the proposed theories.

关键词： T-S fuzzy model descriptor system Sliding mode control Time-delay

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Optimal time-varying Kalman filter for descriptor system with random one-step measurement delay

Optimal time-varying Kalman filter for descriptor system wit...

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第32届中国控制与决策会议

作者： Hao Shen Yinfeng Dou Chenjian Ran Department of Automation Heilongjiang University Key Laboratory of Information Fusion Estimation and Detection

For the linear stochastic descriptor system with random one-step measurement delays,the optimal timevarying Kalman filtering is *** singular value decomposition（SVD） method,the derandomization approach and the augmented state approach are presented,which are applied to transform the descriptor system with random one-step measurement delay to the standard non-descriptor system with fictitious white *** the Kalman filtering and the relation of the new and original systems,the corresponding Kalman filter and filtering error variances are presented.A simulation example about circuits system verifies the correctness of the proposed results.

关键词： descriptor system optimal Kalman filter random one-step measurement delay

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Robust steady-state Kalman filter for descriptor system with random one-step measurement delays and uncertain noise variances

Robust steady-state Kalman filter for descriptor system with...

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第三十九届中国控制会议

作者： Yinfeng Dou Chenjian Ran Yuan Gao Department of Automation Heilongjiang University Key Laboratory of Information Fusion Estimation and Detection

For the linear stochastic descriptor system with random one-step measurement delays and uncertain noise variances,the robust steady-state Kalman predictor is addressed. By new augmented state approach, the original system is transformed to the standard systems without measurement delays. The singular value decomposition（SVD） method, the randomization approach and the augmented state approach are presented, which are applied to transform the descriptor system with random one-step measurement delay to the standard non-descriptor system with fictitious white noises. Applying the presented approaches, the minimax robust steady-state Kalman predictor is presented in the sense that its actual prediction error variance is guaranteed to have the corresponding minimal upper bound for all admissible uncertainties. Their robustness is proved by the Lyapunov equation approach. A simulation example about circuits system verifies the correctness of the proposed results.

关键词： descriptor system robust Kalman filter random one-step measurement delay

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