An adaptive tuned mass damper based on the emulation of positive and negative stiffness with an MR damper

SUMMARYA negative stiffness damper (NSD) is proposed, and its performance on suppressing stay cable vibrations is investigated by numerical simulations and experimental tests. First, the NSD consists of two pressed springs and an oil damper. The two pressed springs are attached perpendicularly to the piston rod of the oil damper in symmetrical configuration. Mechanical model of this damper is derived according to the geometrical configuration and validated experimentally. Considering the simplified model of single-mode vibration of a cable, the cable frequency with the NSD is investigated theoretically by average method, and the lower limit on the pressed degree of two springs is proposed. Numerical examples of cable with NSD and oil damper under sinusoidal excitations are conducted. The NSD shows the superior reduction performance of both amplitudes in time history and peak values of frequency response. A series of single-mode and multi-mode cable vibration control experiments are carried out to evaluate mitigation performance achieved by the NSD. The results indicate that this NSD can provide larger additional modal damping ratio to the cable regardless of single-mode and multiple-mode vibration. Thus, this NSD achieves further reduction of the cable than the oil damper through negative stiffness behavior, instead of complex active or semi-active devices with real-time feedback.

Section: Introductionmentioning

confidence: 99%

Modeling and control performance of a negative stiffness damper for suppressing stay cable vibrations

Zhou

2015

“…Similar numerical and experimental investigations including hybrid testing were conducted in, for example, , for the vibration reduction of buildings equipped with controlled MR dampers. Controlled MR dampers have also been installed in tuned mass dampers in order to make these passive devices adaptive as, for example, proposed in .…”

Section: Introductionmentioning

confidence: 99%

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

Weber

Bhowmik

Høgsberg

2013

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...

“…Boston et al investigate semi-active damping of cables and found that optimal damping force consists of friction force and a spring force with negative stiffness [9]. The same negative damping mechanism was applied to tuned mass dampers (TMDs), and numerical simulations demonstrated its priority over conventional TMDs with fixed spring and damping parameters [10]. The control strategy of MR damper dependent on displacement and direction of motion was adopted in base-isolated bridges [11]; the resultant hysteretic loops were theoretically and numerically similar to those in [9] though experimentally appeared a little different to simulated ones probably because of time lag of damper displacement response to the command.…”

Section: Introductionmentioning

confidence: 99%

Seismic performance of structures incorporating magnetorheological dampers with pseudo-NEGATIVE STIFFNESS

Shi

2011

SUMMARY Pseudo‐negative stiffness control is a control scheme that is aimed to track, in a passive energy dissipation fashion, a target spring force with negative stiffness when possible. In this study, it is proved that systems with pseudo‐negative stiffness control have the property of homogeneity even though they are nonlinear systems. The harmonic response analyses reveal that the pseudo‐negative stiffness reduces the resonant frequency of the system. Seismic response spectrum analyses show that both acceleration and displacement can be reduced with the pseudo‐negative stiffness control when the structural period is long and damping level is not high. Pseudo‐negative stiffness control of a five‐story base‐isolated structure incorporating magnetorheological damper is studied through analytical and real‐time hybrid test methods. The results show that displacement and acceleration responses with pseudo‐negative stiffness control are lower than those with passive‐off control and isolator alone, whereas the displacement response with pseudo‐negative stiffness is greater than the passive‐on control. Copyright © 2011 John Wiley & Sons, Ltd.