On co-design of filter and fault estimator against randomly occurring nonlinearities and randomly occurring deception attacks

Hu, Jun; Liu, Steven; Ji, Donghai; Li, Shanqiang

doi:10.1080/03081079.2015.1106730

Cited by 59 publications

(23 citation statements)

References 36 publications

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“…In addition, it is worth noting that, due to the influence of internal and external environmental factors, nonlinearity always exists in the actual system. At present, the control problem of the network system with nonlinearity is widely concerned [36]. Since the nonlinear perturbation phenomena may vary arbitrarily, Bernoulli distribution is more appropriate to describe the randomly occurring nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Boundedness Control for Nonlinear Networked Systems with Randomly Occurring Multi-Distributed Delays and Missing Measurements

Hou

Chen

2018

Mathematical Problems in Engineering

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This paper investigates the stochastic finite-time ∞ boundedness problem for nonlinear discrete time networked systems with randomly occurring multi-distributed delays and missing measurements. The randomly occurring multi-distributed delays and missing measurements are described as Bernoulli distributed white noise sequence. The goal of this paper is to design a full-order output-feedback controller to guarantee that the corresponding closed-loop system is stochastic finite-time ∞ bounded and with desired ∞ performance. By constructing a new Lyapunov-Krasovskii functional, sufficient conditions for the existence of outputfeedback are established. The desired full-order output-feedback controller is designed in terms of the solution to linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the validity of the designed method.

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Section: Introductionmentioning

confidence: 99%

Finite-Time Boundedness Control for Nonlinear Networked Systems with Randomly Occurring Multi-Distributed Delays and Missing Measurements

Hou

Chen

2018

Mathematical Problems in Engineering

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“…For the co-design problem of state and fault estimator using stochastic system model, a robust fault estimation filter design was proposed in terms of Riccati-like difference equations in [44,45]. Using the assumption that the sampling interval was sufficiently small, it was supposed that the fault difference item was too small to be neglected.…”

Section: Problem Statementmentioning

confidence: 99%

“…However, in practice, faults always generate a great amplitude change of a certain time, especially when time-varying faults occur. Compared with the assumption in [44,45], it is clear that time-varying fault model described in Equation (6) covers the results of constant faults as a special case, which is less restrictive.…”

Section: Problem Statementmentioning

confidence: 99%

Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts

2018

Sensors

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Wireless sensors have many new applications where remote estimation is essential. Considering that a remote estimator is located far away from the process and the wireless transmission distance of sensor nodes is limited, sensor nodes always forward data packets to the remote estimator through a series of relays over a multi-hop link. In this paper, we consider a network with sensor nodes and relay nodes where the relay nodes can forward the estimated values to the remote estimator. An event-triggered remote estimator of state and fault with the corresponding data-forwarding scheme is investigated for stochastic systems subject to both randomly occurring nonlinearity and randomly occurring packet dropouts governed by Bernoulli-distributed sequences to achieve a trade-off between estimation accuracy and energy consumption. Recursive Riccati-like matrix equations are established to calculate the estimator gain to minimize an upper bound of the estimator error covariance. Subsequently, a sufficient condition and data-forwarding scheme are presented under which the error covariance is mean-square bounded in the multi-hop links with random packet dropouts. Furthermore, implementation issues of the theoretical results are discussed where a new data-forwarding communication protocol is designed. Finally, the effectiveness of the proposed algorithms and communication protocol are extensively evaluated using an experimental platform that was established for performance evaluation with a sensor and two relay nodes.

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“…It is well recognized that the existence of the randomly occurring incomplete information would highly degrade the system performance if not handled properly. So far, a series of estimation and filtering schemes has been developed for networked systems with randomly occurring incomplete information in the literature, and great efforts have been made to deal with the randomly occurring nonlinearities in [49], [95]- [99], the randomly occurring uncertainties in [94], [97], the randomly occurring sensor saturations in [40], [72], the randomly occurring sensor delays in [31], [32], [38], [100], [101], the randomly occurring signal quantization in [41], [102], and the randomly occurring faults in [103]. Accordingly, several techniques for analysis and synthesis of the networked systems have been given, including innovation analysis approach [31], [32], linear matrix inequality approach [97], Hamilton-Jacobi-Isaacs inequality method [100], difference linear matrix inequality method [41], Riccati difference equation approach [101], [102], and game theory method [54].…”

Section: E Randomly Occurring Incomplete Informationmentioning

confidence: 99%

Estimation, filtering and fusion for networked systems with network-induced phenomena: New progress and prospects

et al. 2016

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In this paper, some recent advances on the estimation, filtering and fusion for networked systems are reviewed. Firstly, the network-induced phenomena under consideration are briefly recalled including missing/fading measurements, signal quantization, sensor saturations, communication delays, and randomly occurring incomplete information. Secondly, the developments of the estimation, filtering and fusion for networked systems from four aspects (linear networked systems, nonlinear networked systems, complex networks and sensor networks) are reviewed comprehensively. Subsequently, some recent results on the estimation, filtering and fusion for systems with the network-induced phenomena are reviewed in great detail. In particular, some latest results on the multiobjective filtering problems for time-varying nonlinear networked systems are summarized. Finally, conclusions are given and several possible research directions concerning the estimation, filtering, and fusion for networked systems are highlighted.

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On co-design of filter and fault estimator against randomly occurring nonlinearities and randomly occurring deception attacks

Cited by 59 publications

References 36 publications

Finite-Time Boundedness Control for Nonlinear Networked Systems with Randomly Occurring Multi-Distributed Delays and Missing Measurements

Finite-Time Boundedness Control for Nonlinear Networked Systems with Randomly Occurring Multi-Distributed Delays and Missing Measurements

Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts

Estimation, filtering and fusion for networked systems with network-induced phenomena: New progress and prospects

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