Optimal semi-active damping of cables: evolutionary algorithms and closed-form solutions

Boston, C; Weber, Felix; Guzzella, Lino

doi:10.1088/0964-1726/18/5/055006

Cited by 25 publications

(38 citation statements)

References 19 publications

(24 reference statements)

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“…The third control law under consideration is amplitude proportional friction damping with negative stiffness (FDNS) at a tuning that clipping is not mandatory. The authors of showed that this is a very effective semi‐active damping strategy that is close to the solution of the clipped optimal control. Then, the experimentally obtained force tracking for the three control laws are shown, and the resulting effective damping ratios of the shear frame are presented and compared with the simulated results.…”

Section: Introductionmentioning

confidence: 85%

Extended neural network-based scheme for real-time force tracking with magnetorheological dampers

Weber

Bhowmik

Høgsberg

2013

Struct. Control Health Monit.

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This paper validates numerically and experimentally a new neural network-based real-time force tracking scheme for magnetorheological (MR) dampers on a five-storey shear frame with MR damper. The inverse model is trained with absolute values of measured velocity and force because the targeted current is a positive quantity. The validation shows accurate results except of small current spikes when the desired force is in the vicinity of the residual MR damper force. In the closed-loop, higher frequency components in the current are triggered by the transition of the actual MR damper force from the pre-yield to the post-yield region. A control-oriented approach is presented to compensate for these drawbacks. The resulting control force tracking scheme is validated for the emulation of viscous damping, clipped viscous damping with negative stiffness, and friction damping with negative stiffness.The tests indicate that the proposed tracking scheme works better when the frequency content of the estimated current is close to that of the training data. The LuGre friction model was adopted as observer in [18] to solve the force tracking task. This short review on existing real-time force tracking schemes shows that the nonmodel-based Heaviside step function approach only works with force feedback; the Dahl model leads to precise current estimation only in special cases, and the LuGre friction model can only be used as observer because this approach cannot be inverted. In this study, the real-time force tracking task without force feedback is therefore investigated by the adoption of soft-computing techniques that allow modeling the inverse MR damper dynamics directly and thereby circumvent the aforementioned drawbacks.Besides the fuzzy logic approach that is used in [19] to directly estimate the inverse MR damper behavior, the neural network method is seen to be able to capture the nonlinear inverse MR damper dynamics. Recurrent neural network models were constructed in [20] to emulate both the forward and inverse MR damper dynamics. Both models take the previous values of the estimated force and voltage, respectively, as inputs among other states. The validation of the inverse model shows some high frequency spikes in the estimated voltage. In the work of Xia [21], the inverse MR damper behavior was modeled by using a multilayer perceptron optimal neural network and system identification. The inverse model is trained and validated with simulated data taking into account the previous values of the voltage. The authors of [22] studied the modeling of the inverse MR damper dynamics using feedforward and recurrent neural networks. For the targeted constant voltage of 1.5 V, the predicted voltage showed spikes of up to AE0.17 V at a frequency that seems to be equal to the damper motion frequency. If the targeted voltage is a sinusoidal function with constant frequency, the time history of the estimated voltage does not describe a pure sine, and thereby, the resulting error is larger than AE0.17 V. In contrast, the forward mo...

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Section: Introductionmentioning

confidence: 85%

Extended neural network-based scheme for real-time force tracking with magnetorheological dampers

Weber

Bhowmik

Høgsberg

2013

Struct. Control Health Monit.

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“…This triggered the development of semi-active cable damping systems that are mainly based on semi-actively controlled magnetorheological (MR) dampers due to their suitable force range and reliability. The damping systems presented in [14][15][16][17][18][19][20][21][22][23][24][25][26] are based on optimal control, passive-on control, semi-active friction damping with negative stiffness, clipped viscous damping with negative stiffness and represent a small selection of the vast variety of MR damper based cable damping systems.…”

Section: Cable Damping Systemsmentioning

confidence: 99%

Amplitude and frequency independent cable damping of Sutong Bridge and Russky Bridge by magnetorheological dampers

Weber

Distl

2014

Struct. Control Health Monit.

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SUMMARY Two control approaches for magnetorheological (MR) dampers on cables based on collocated control without state estimation are formulated, which generate amplitude and frequency independent cable damping: cycle energy control and controlled viscous damping (CVD). The force tracking is solved by the inverted Bingham model whose parameters are fitted as function of current and frequency. Cycle energy control and CVD are experimentally validated by hybrid simulations and free decay tests on stay cables of the Sutong Bridge, China, and the Eiland Bridge, the Netherlands. The implementation of CVD on the Russky Bridge, Russia, includes two novelties: the force tracking also takes the actual MR damper temperature into account to ensure precise force tracking for MR damper temperatures −40 to +60 °C and the decentralised real‐time control units with pulse width current modulation are installed next to each MR damper to avoid long direct current (DC) power lines with associated losses and thereby minimise power consumption. Copyright © 2014 John Wiley & Sons, Ltd.

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“…However, because the analytical method can only take a few structural parameters into consideration and has been applied almost exclusively to simply supported boundary condition (BC), the reliability, and applicability of the calculation results are bound to be affected. To consider the influence of various factors comprehensively, the complex cable system (CCS) can also be analyzed by some numerical methods including finite element method (FEM), Galerkin method, finite difference method, and so forth. Among them, the FEM is more commonly used but its calculation accuracy depends on the number of elements and the quality of the shape function, whose accuracy and computational efficiency are a set of irreconcilable contradiction.…”

Section: Introductionmentioning

confidence: 99%

Unified modal analysis of complex cable systems via extended dynamic stiffness method and enhanced computation

Dan

Han

Cheng

et al. 2019

Struct Control Health Monit

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Summary With the increase of the span and height of modern engineering structures, the design length and complexity of the cable structure are constantly increasing, whose dynamic problem has become the key to structural design, performance monitoring and maintenance, and vibration control. Therefore, it is necessary to study and develop a unified dynamic analysis theory for complex cable system to meet the requirements of calculation accuracy and efficiency. In view of this, a unified dynamic analysis method for dynamic analysis of complex cable system is proposed in this paper on the basis of the classical dynamic stiffness method. In this paper, the dynamic stiffness method has been enhanced in multiple aspects, which not only retains the advantages of high computational efficiency and wide application range but also overcomes its technical bottlenecks in analysis of shallow‐sag cable system considering the damping effect, composite cable systems, and multisegment cable systems. The proposed method can not only be used to the structural design of the complex cable system but also be extended to the vibration control of the system during the service period.

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Optimal semi-active damping of cables: evolutionary algorithms and closed-form solutions

Cited by 25 publications

References 19 publications

Extended neural network-based scheme for real-time force tracking with magnetorheological dampers

Extended neural network-based scheme for real-time force tracking with magnetorheological dampers

Amplitude and frequency independent cable damping of Sutong Bridge and Russky Bridge by magnetorheological dampers

Unified modal analysis of complex cable systems via extended dynamic stiffness method and enhanced computation

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