Neighborhood‐based distributed robust unknown input observer for fault estimation in nonlinear networked systems

Rahimi, Farshad; Ahmadpour, Shirin

doi:10.1049/cth2.12278

Cited by 12 publications

(2 citation statements)

References 38 publications

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“…Lastly, delay‐dependent sufficient conditions are derived by means of linear matrix inequality to prove convergence to optimal solutions. In order to increase the usefulness of the proposed method for the practical systems in future studies, this work can be extended to include the following issues: (1) Considering the quantization effects in exchanging information within a network [33]; (2) Considering non‐convex optimization problem [34]; (3) Considering uncertainty or disturbance in the dynamics of each agent [35].…”

Section: Discussionmentioning

confidence: 99%

Estimating tolerable communication delays for distributed optimization problems in control of heterogeneous multi‐agent systems

Rahimi,

Mahboobi Esfanjani

2023

IET Control Theory & Appl

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This study addresses the problem of distributed optimization in control of heterogeneous linear multi‐agent systems. Instead of assuming a perfect communication medium as in many existing approaches, two important issues arising from communication networks are considered. First, the existence of communication delays is assumed when each agent receives information from its neighbors. Second, since communication networks are generally unreliable, it is assumed that each agent interacts with other agents through random digraphs. Finally, delay‐dependent sufficient conditions are derived in the form of linear matrix inequalities (LMIs) to prove convergence to optimal solutions. Numerical simulation results are analyzed to demonstrate the effectiveness of the proposed approach.

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Section: Discussionmentioning

confidence: 99%

Estimating tolerable communication delays for distributed optimization problems in control of heterogeneous multi‐agent systems

Rahimi,

Mahboobi Esfanjani

2023

IET Control Theory & Appl

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“…Wireless sensor networks (WSNs), as a new generation sensor network, have been widely used in agricultural monitoring [1], fault detection [2], and mine safety [3]. In the past few decades, various wireless localization techniques are widely used with the development of wireless sensor network technology, such as WiFi, Bluetooth low energy (BLE), ZigBee, and ultra‐wideband (UWB) (see refs.…”

Section: Introductionmentioning

confidence: 99%

Received signal strength indicator‐based set‐membership filtering indoor localization under multipath effect

Yang

Dong

Shang

et al. 2022

IET Control Theory & Appl

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The indoor moving target localization based on the received signal strength indicator is studied in this paper. By introducing filtering algorithms, a novel dynamic parameters setmembership filtering (DPSMF) is proposed to reduce the interference of the multipath effect and noises. First, the higher-order remainder is included in the bounded range based on the interval mathematics method to improve the linearization accuracy of the Taylor series expansion of the measurement function. Second, the parameters to be determined in the channel model are set to local dynamic parameters, which are obtained by solving a particular semi-definite programming problem. Third, the optimized localization estimations of the target node at each sampling instant and the ellipsoid set containing the real state of the system are obtained based on the DPSMF. Finally, an example is given to verify the effectiveness of the proposed DPSMF algorithm.

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Fault‐tolerant control design for stochastic distribution control systems based on k‐step fault estimation

Yuan,

Yao

2023

Asian Journal of Control

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A novel scheme of fault‐tolerant control (FTC) and fault estimation (FE) for the stochastic distribution control (SDC) system with disturbance is investigated. The output probability density function (PDF) is modelled by the weight vector of the B‐spline neural network with the given basis function, and control of output probability density function can be converted to control of the weight vector of the B‐spline neural network. A k‐step fault estimation algorithm aiming at enhancing the accuracy of fault estimation is first applied to the stochastic distribution control system. Subsequently, a dynamic output feedback fault‐tolerant control algorithm is constructed by using the k‐step fault estimation information to guarantee that the target weight vector can be still approximated by the output weight vector in case of actuator fault. A simulation example is used to confirm the availability of the presented method.

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Neighborhood‐based distributed robust unknown input observer for fault estimation in nonlinear networked systems

Cited by 12 publications

References 38 publications

Estimating tolerable communication delays for distributed optimization problems in control of heterogeneous multi‐agent systems

Estimating tolerable communication delays for distributed optimization problems in control of heterogeneous multi‐agent systems

Received signal strength indicator‐based set‐membership filtering indoor localization under multipath effect

Fault‐tolerant control design for stochastic distribution control systems based on k‐step fault estimation

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