Distributed wireless-based control strategy through Selective Negative Derivative Feedback algorithm

Debattisti, Nicola; Bacci, Maria Laura; Cinquemani, Simone

doi:10.1016/j.ymssp.2020.106742

Cited by 11 publications

(12 citation statements)

References 27 publications

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“…So, in overall based on the maximum damping method, the NDF parameters are defined by equations ( 9)- (11). All of these parameters are dependent on the closed loop damping (η) and therefore these equations are rewritten dependent only closed loop damping in the below table.…”

Section: Maximum Damping Methodsmentioning

confidence: 99%

“…The proposed algorithm is very interesting, but it is very hard to apply on any system. Debattisti et al [11], evaluated distributed wireless-based control strategy through selective NDF algorithm. Also, one important factor in smart structures is evaluating sensor/actutaor distributions and segmentation on the structures which has been studied by many researchers as well [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Designing negative derivative feedback controller based on maximum damping and H ₂ method

Jamshidi¹,

Collette²

2022

Smart Mater. Struct.

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In this paper, a straightforward procedure is presented for optimal design of negative derivative feedback (NDF) controller with maximum damping and H_2 optimization method. NDF is a controller, which works as a band-pass filter, cutting off the control action far from the natural frequencies associated with the controlled modes and reducing spillover effect. Since it is a bandpass filter, it can effectively control the lower or higher frequency disturbances. It is also implementable on vibration mitigation applications with high performance. For this end, a simple one degree of freedom system is considered and afterward, the controller parameters are extracted dependent on closed loop damping. The H_2 method is used to calculate the optimal value of closed loop damping. The effect of changing the controller parameters on the system response are evaluated and discussed in detail. Also, the control effort for various closed loop damping has been calculated and compared with performance index of controller. A detailed comparison between performance and control effort were also presented. The results show high impact of NDF controller on vibration mitigation and its applicability to employ on various systems.

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Section: Maximum Damping Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Designing negative derivative feedback controller based on maximum damping and H ₂ method

Jamshidi¹,

Collette²

2022

Smart Mater. Struct.

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“…Wireless sensors have been developed for monitoring activities in various complex fields, such as monitoring of wind-induced vibration on transmission line conductors [14], dynamics of freight wagon vehicle and the infrastructure [15,16], and historical buildings [17]. Some applications of wireless sensors can also be found in the active vibration control field [18,19].…”

Section: Introductionmentioning

confidence: 99%

Development and Field Validation of Wireless Sensors for Railway Bridge Modal Identification

et al. 2023

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Bridges are strategic infrastructures which are subject to degradation during their lifetime. Therefore, structural health monitoring is becoming an essential tool in this field to drive maintenance activities. Conventional vibration monitoring systems relying on wired sensors present several limitations for continuous monitoring projects on a huge number of structures. In this work, a smart wireless monitoring system is developed for bridge modal identification with the aim of providing an alternative tool to wired sensors in this field. The main peculiarities of the designed wireless accelerometers are the low cost, the ease of installation on the structure, and the long-term autonomy granted by the use of energy harvesting techniques. To assess their measurement performance, some prototypes were installed for a field test on a railway bridge and significant data were acquired. Through the processing of the collected data, bridge main natural frequencies were estimated, and their values were in good agreement with the reference ones obtained with a conventional system. The assessment of the developed solution paves the way to the instrumentation of many bridges with the aim of performing continuous monitoring activities using simple diagnostic indicators, such as the variation of frequencies in time.

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“…This wireless data sharing between devices has been already used in a control system, where two wireless nodes were considered [10,11]. A Selective Negative Derivative Feedback (SNDF) control law has been implemented in [10].…”

Section: Introductionmentioning

confidence: 99%

Automatic Decentralized Vibration Control System Based on Collaborative Stand-Alone Smart Dampers

2023

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In many structures, undesired noise and vibrations generated by external sources represent a huge problem in terms of structural damage and comfort. Active vibration absorbers can be used to dynamically suppress vibrations, by increasing the damping of the system. A wireless smart active damper has been developed to perform this task and some automated functionalities have been implemented to perform the identification of the structure on which it is mounted on. The sharing of information between wireless sensors represents one of the most interesting features of this kind of control system. In this work, a procedure to estimate the nondimensional damping and modal amplitude for each wireless sensor location and each vibration mode is studied. Then, the information obtained by each sensor in the identification phase are used to implement a coordinated control strategy, which is based on a modified version of the Efficient Modal Control (EMC). Such control strategy implements the low level Selective Negative Derivative Feedback control law and modulates the control gains of each actuator and controlled mode pair in order to get an effective vibration reduction. The tuning procedure represents the next step of the algorithm, in which the evaluation of the introduced damping and the maximum applicable gains are derived; finally, the proposed solution is validated with experimental results on a simply-supported beam.

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Distributed wireless-based control strategy through Selective Negative Derivative Feedback algorithm

Cited by 11 publications

References 27 publications

Designing negative derivative feedback controller based on maximum damping and H ₂ method

Designing negative derivative feedback controller based on maximum damping and H ₂ method

Development and Field Validation of Wireless Sensors for Railway Bridge Modal Identification

Automatic Decentralized Vibration Control System Based on Collaborative Stand-Alone Smart Dampers

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Distributed wireless-based control strategy through Selective Negative Derivative Feedback algorithm

Cited by 11 publications

References 27 publications

Designing negative derivative feedback controller based on maximum damping and H 2 method

Designing negative derivative feedback controller based on maximum damping and H 2 method

Development and Field Validation of Wireless Sensors for Railway Bridge Modal Identification

Automatic Decentralized Vibration Control System Based on Collaborative Stand-Alone Smart Dampers

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Product

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Designing negative derivative feedback controller based on maximum damping and H ₂ method

Designing negative derivative feedback controller based on maximum damping and H ₂ method