Fault tolerant plug and play vibration control in building structures

This paper investigates a design framework for a class of distributed interconnected systems, where a fault diagnosis scheme and a cooperative fault-tolerant control scheme are included. First of all, fault detection observers are designed for the interconnected subsystems, and the detection results will be spread to all subsystems in the form of a broadcast. Then, to locate the faulty subsystem accurately, fault isolation observers are further designed for the alarming subsystems in turn with the aid of an adaptive fault estimation technique. Based on this, the fault estimation information is used to compensate for the residuals, and then isolation decision logic is conducted. Moreover, the cooperative fault-tolerant control unit, where state feedback and cooperative compensation are both utilized, is introduced to ensure the stability of the whole system. Finally, the simulation of intelligent unmanned vehicle platooning is adopted to demonstrate the applicability and effectiveness of the proposed design framework.

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“…According to Equation (15), the necessary optimality conditions, obtained from the optimal control theory [ 28 ], are

…”

Section: Resultsmentioning

confidence: 99%

A Distributed Fault Diagnosis and Cooperative Fault-Tolerant Control Design Framework for Distributed Interconnected Systems

Zhang

Wang

et al. 2022

Sensors

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“…The reference model is a three-story shear-frame structure whose vibration responses is controlled by a linear controller designed by the linear quadratic regulator (LQR) method, in which 𝐑 = 10 −9 𝐈 and 𝐐 = 𝐈. The mass, stiffness, and damping matrices are as follows (Chung et al, 1989;Larbah & Patton, 2010):…”

Section: Reference Model and Unknown Buildingmentioning

confidence: 99%

“…The reference model is a three‐story shear‐frame structure whose vibration responses is controlled by a linear controller designed by the linear quadratic regulator (LQR) method, in which

\mathbf{R}\hspace*{0.28em}={10}^{-9}\hspace*{0.28em}\mathbf{I}

and

{\bf{Q}}{\rm{\;}} = {\rm{\;}}{\bf{I}}

. The mass, stiffness, and damping matrices are as follows (Chung et al., 1989; Larbah & Patton, 2010):

\begin{equation} \def\eqcellsep{&}\begin{array}{l} {\bf{M}}\; = \left[ { \def\eqcellsep{&}\begin{array}{@{}*{3}{c}@{}} 6&0&0\\ 0 \quad &6 \quad & 0\\ 0 \quad &0 \quad &6 \end{array} } \right]{\rm{\;}} \times {10^3}\,{\rm{kg}},\\ {\bf{K}}\; = \left[ { \def\eqcellsep{&}\begin{array}{@{}*{3}{c}@{}} {3.4}&{ - 1.8}&0\\ { - 1.8}&{3.4}&{ - 1.6}\\ 0&{ - 1.6}&{1.6} \end{array} } \right]\; \times {10^6}{\rm{N/m}},{\rm{and}}\\ {\bf{C}}\; = \left[ { \def\eqcellsep{&}\begin{array}{@{}*{3}{c}@{}} {12.4}&{ - 5.16}&0\\ { - 5.16}&{12.4}&{ - 4.59}\\ 0&{ - 4.59}&{7.2...

…”

Section: Numerical Simulationmentioning

confidence: 99%

Seismic adaptive control of building structures with simultaneous sensor and damper faults based on dynamic neural network

Naderpoor

Taghikhany

2021

Computer aided Civil Eng

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The use of seismic control systems in building structures requires simultaneous attention to uncertainties in model parameters, measurement noises, faults on sensors and dampers, and earthquake input. The present study suggests a procedure to resolve the complications of these issues in semi-active control of building structures. To this end, the effects of faults on sensors and dampers are decoupled by using transfer matrices. The sensor fault and the structure's state are estimated by a dynamic neural network (DNN)-based observer. Later, parametric uncertainty in the structure's model and fault on dampers are atoned by an adaptive controller that guarantees the stability of the system during an earthquake. In this controller, DNN is used to concurrently identify and compensate dampers' faults. The effectiveness of the proposed method was confirmed by numerical simulation of a three-story structure with magneto-rheological dampers.

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“…studied their decentralized algorithm for local failure in a sub-system of a twenty-story benchmark building. Larbah and Patton (2010) evaluated their hierarchical control model for different scenarios of actuator fault in a three-story building model. Palacios-Quinonero et al (2012), also studied the performance of their proposed semi-decentralized overlapping approach for two adjacent buildings in the case of partial failures of the control system.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode fault detection and fault-tolerant control of smart dampers in semi-active control of building structures

Fallah

Taghikhany

2015

Smart Mater. Struct.

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Recent decades have witnessed much interest in the application of active and semi-active control strategies for seismic protection of civil infrastructures. However, the reliability of these systems is still in doubt as there remains the possibility of malfunctioning of their critical components (i.e. actuators and sensors) during an earthquake. This paper focuses on the application of the sliding mode method due to the inherent robustness of its fault detection observer and faulttolerant control. The robust sliding mode observer estimates the state of the system and reconstructs the actuators' faults which are used for calculating a fault distribution matrix. Then the fault-tolerant sliding mode controller reconfigures itself by the fault distribution matrix and accommodates the fault effect on the system. Numerical simulation of a three-story structure with magneto-rheological dampers demonstrates the effectiveness of the proposed fault-tolerant control system. It was shown that the fault-tolerant control system maintains the performance of the structure at an acceptable level in the post-fault case.

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Fault tolerant plug and play vibration control in building structures

Cited by 4 publications

References 6 publications

A Distributed Fault Diagnosis and Cooperative Fault-Tolerant Control Design Framework for Distributed Interconnected Systems

A Distributed Fault Diagnosis and Cooperative Fault-Tolerant Control Design Framework for Distributed Interconnected Systems

Seismic adaptive control of building structures with simultaneous sensor and damper faults based on dynamic neural network

Sliding mode fault detection and fault-tolerant control of smart dampers in semi-active control of building structures

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