Research Article  Open Access
Wei Zhu, Xiaoting Rui, "Semiactive Vibration Control Using a Magnetorheological Damper and a Magnetorheological Elastomer Based on the BoucWen Model", Shock and Vibration, vol. 2014, Article ID 405421, 10 pages, 2014. https://doi.org/10.1155/2014/405421
Semiactive Vibration Control Using a Magnetorheological Damper and a Magnetorheological Elastomer Based on the BoucWen Model
Abstract
A vibration control system is put forward using a magnetorheological damper (MRD) and a magnetorheological elastomer (MRE) connected in series. In order to model the hysteresis of the MRD, a BoucWen model and a corresponding parameter identification method are developed for the MRD. The experimental results validate the proposed BoucWen model that can predict the hysteretic behavior of the MRD accurately. The role of the MRE is illustrated by an example of a single degreeoffreedom system. A semiactive vibration control strategy of the proposed vibration control system is proposed. To validate this new approach, experiments are conducted and the results highlight significantly improved vibration reduction effect of the proposed vibration control system than the vibration control system only using the MRD.
1. Introduction
Magnetorheological dampers (MRDs) hold promise for vibration control since their properties can be adjusted in real time, and unlike active devices they do not inject energy into the system being controlled and have relatively low power requirements. The MRDs, using MR fluids that exhibit controllable yield characteristics, produces sizeable damping force for small input current. Being an energy dissipation device that cannot add mechanical energy to the structural system, an MR damper is also very stable and fail safe. MR fluid contains a suspension of iron particles in a carrier fluid such as oil [1].
The BoucWen model [2] describes the hysteretic behavior of MR dampers except near small velocities. This shortcoming was rectified by Spencer et al. [3] in their modified BoucWen model, where in additional damping and stiffness elements were used to model the lowvelocity behavior and the accumulator, respectively, and voltage dependent parameters were introduced. Dominguez et al. [4] developed a currentfrequencyamplitude dependent BoucWen model and an identification method. Other damper models include the phasetransition model of Wang and Kamath [5] and modified LuGre friction model of Jiménez and ÁlvarezIcaza [6] and Sakai et al. [7].
Various controller designs have been used with MR dampers. Predicting the applied voltage that produces a desired damper force is difficult due to the noninvertible forcevoltage dynamics. Hence, different voltage laws have been considered. Xu and Shen [8] used bistate control strategies with a Bingham damper model, onoff current law, and neural network response prediction. Dyke et al. [9] implemented acceleration feedback linear quadratic Gaussian (LQG) control, using the modified BoucWen model, to obtain the desired optimal damper force using measured accelerations, displacements, and damper force. Based on the classical skyhook damping a novel semiactive control strategy, well suited for use in drive systems, is presented by Frey et al. [10]. Prabakar et al. [11] applied a half car model for simulating the semiactive suspension system. They modeled the parameters of a MRD by the modified BoucWen model and determined that they fit the hysteretic behavior and put forward optimal semiactive preview control. Weber [12] presented a BoucWen modelbased control scheme which allows tracking the desired control force in realtime with magnetorheological (MR) dampers without feedback from a force sensor.
However, the MRD can only change its damping and the response time is generally slower than 20 ms which could make the highfrequency performance of the vibration control system decrease [9].
Magnetorheological elastomers (MREs), like MR fluids, exploit magnetic forces between dispersed micronsized ferromagnetic particles to produce a material with instantaneously adjustable properties. However in MR fluids the particles are dispersed within a liquid and operate in a postyield regime, while in MREs the particles are part of a structured elastomer matrix in a preyield regime [13]. Rigbi did the earliest work with what could be considered MRE materials but dealt mainly with the magnetic properties of a strained isotropic sample [14]. Jolly after considerable experience with MR fluids developed an anisotropic MRE, where spherical iron particles were aligned by an external magnetic field into long parallel chains within the curing rubber [15]. MREs can be used to make up for the shortcomings of MRDs in vibration control system due to the adjustable properties of their stiffness.
The paper is organized as follows. Section 1 contains a brief introduction, literature review, and aims and scope of the paper; Section 2 describes a vibration control device using a MRD and a MRE connected in series; Section 3 describes the BocuWen model and parameter identification method for MRDs; a MRE device is put forward in Section 4; a semiactive vibration control strategy is proposed in Section 5; Section 6 presents experimental results and discussions, including comparisons with available results; and Section 7 contains the conclusions and future scope.
2. Vibration Control System
Figure 1 shows a vibration control system using a MRD and a MRE connected in series. In the design, the MRD is used to reduce the largerange and lowfrequency vibration; the MRE is used to reduce the smallrange and highfrequency vibration.
(a) Photograph
(b) Schematic diagram
The dynamic equation of the vibration control device can be given by where . The system matrices are where is the force of the MRD; and are the stiffness and viscous damping coefficient, respectively.
3. MRDs
3.1. BoucWen Model of MRDs
In order to control the force of the MRD, it is essential to propose a model for MRDs. The BoucWen model of MRDs is given by [1] where and are the damper displacement and velocity; is the BoucWen hysteresis operator; “” at the top of variables represents the first order derivative of the variables with respect to time; is the current applied to the MRD; and are the stiffness and damping function of the efficient current, respectively; is function related to the MR material yield stress; is the initial displacement which can be measured; , , , and are the parameters of the BoucWen hysteresis operator.
Let . is the hysteresis force. Equation (3) can be rewritten as
In order to use the BoucWen model given by (4) and (5) to simulate the hysteretic behaviour of the MRD, the functions , , , , and and the parameters and need to be identified.
3.2. Parameter Identification Method
The initial displacement can be obtained by measuring the displacement of the rod. Let the current be a constant. The functions , , , , and are the constants , , , , and , respectively. Consider the corresponding forces and from the MRD with two periodical displacements and , which are related by where is a constant. We have where and are the hysteresis force. According to (5) and (6), .
Consider a set of points in the hysteresis curve force against displacement determined by (7) and in the hysteresis curve force against displacement determined by (8). With the leastsquares method, the parameter is given by
The BoucWen hysteresis operator given by (5) possesses the symmetrical characteristic [17, 18]. Therefore, we have [19] where and are the minimum and maximum value of the displacement in the th () period, respectively; and are corresponding force; and are corresponding velocity.
With the leastsquares method, the parameter can be given by According to (6), we have where According to (4), the hysteresis operator can be written as Let . According to (14), we have Assume that is the solution of (15). According to (12) and (14), we have When , consider a set of points in , which ensures that the corresponding hysteresis displacement is larger than zero. Then (12) can be rewritten as Let . According to (17), we have According to (18) and the leastsquares method, we have When , consider a set of points in , which ensures that the corresponding hysteresis displacement is larger than zero. Then (12) can be rewritten as Let . According to (21), we have With the leastsquares method, (22) can be rewritten as
According to (20) and (23), the parameters and are given by
According to (9), (11), (16), (19), and (24), under the single current, the parameters , , , , , and can be identified if the periodical displacements and and the corresponding forces and are known. Applying the various currents to the MRD, the corresponding parameters , , , , and can be obtained. With the leastsquares method, the functions , , , , and can be identified.
3.3. Modeling Results
The MRD is subjected to sinusoidal excitations on an electrohydraulic servo fatigue machine (type: LFV 150 kN, the W + B GmbH, Switzerland) to validate the BoucWen model and the corresponding parameter identification method. The primary components of the test setup are shown in Figure 1. The fatigue machine has its own software to collect the data from the data card and use them to plot force versus displacement and force versus velocity graphs for each test. A programmable power (type IT6122, the ITECH Electronic Co, Ltd) supply is used to feed current to the MRD. The damper is fixed to the machine via grippers as shown in the Figure 2. The machine excites the damper’s piston rod sinusoidally, while a load cell measures the force on the damper and a linear variable displacement transducer measures the displacement of the piston rod as well as the relative velocity. Since the identification method uses the values of the derivatives at some points of the experimental data, it is necessary to filter the data before applying the identification algorithm. To this end, a second order filter of the form is used, with _ and , where is the frequency of the input signal.
A comparison between the predicted responses and the corresponding experimental data is provided in Figure 3. The BoucWen model predicts the forcedisplacement behavior of the damper well, and it possesses forcevelocity behavior that also closely resembles the experimental data. Therefore, it is reasonable to believe that the BoucWen model and the corresponding parameter identification method can predict the hysteretic behavior of the MRD accurately.
(a) Force versus displacement
(b) Force versus velocity
4. MRE Device
The MRE device, which is composed of two MREs, coil and two magnetic conductors, is shown in Figure 4. The size of the MRE device can be given by
(a) Structure
(b) Photograph
According to (25), . Therefore, the areas of two MREs are equal, which can make the magnetic induction intensity of two MREs be consistent.
So the total area of MREs can be given by
The middle hole with screw can play the roles of fixed and limited displacement.
The average values of tension/compression modulus and loss factor with current at different loading frequencies (1 Hz, 10 Hz, 20 Hz, and 30 Hz) are shown in Figure 5. represents the complex tension/compressive modulus, which can be expressed as where is the storage modulus and is the loss modulus. The loss factor can be expressed as
(a) Tension/compression modulus
(b) Loss factor
From Figure 5, we have where and are the minimum and maximum value of the storage modulus, respectively; and are the minimum and maximum value of the stiffness, respectively.
The stiffness and damping of the MRE device can be given by where is a stiffness function of the efficient current . Observing Figure 5, we have
Figure 6 shows a singleDOF massdamperspring semiactive vibration control system composed of the MRE device and a mass. Let mass = 5 kg. The bode diagram of the system with the applied various current is shown in Figure 7. From Figure 7, the vibration characteristics of the system can be changed by the various currents. Therefore, the MRE device can reduce vibration when the semiactive vibration control is proposed.
5. Semiactive Vibration Control Strategy
According to (1), the statespace equation of the system can be given by where
The skyhook control [10, 20, 21] is widely used semiactive vibration control. The skyhook control model of the vibration control system is shown in Figure 8. From Figure 8 and according to (32), we have where and are the skyhook damped coefficients.
Consider the actual dynamic responses of the system can be obtained by the sensors. The BoucWen model of the MRD is computed in real time for the constant currents A for the actual displacement and velocity. The corresponding estimated forces of the MRD can be obtained theoretically by calculation. Based on the estimated forces and the desired control force , the control current is derived by piecewise linear interpolation [12, 22]. Therefore, (34) can be rewritten as where is the actual control current of the MRD.
According to (30), (31), and (35), the actual control current of the MRE can be expressed by where is the inverse function of , and its value range is ; is the maximum control current of the MRE.
According to (36) and (37), the actual control currents of the MRD and the MRE can be obtained.
6. Experimental Implementation
In order to experimentally validate the proposed vibration control system and the semiactive vibration control strategy, the schematic and photograph of the experimental setup are shown in Figures 9(a) and 9(b), respectively. According to Figure 9, the experimental setup is composed of the proposed vibration control system, accelerometers (type: CAYD109B, range: 0–50 m/s^{2}, linearity: 99.8%), charge amplifier (type 5018, Kistler Corporation), current source (linearity: 99.2%), vibration table (type: MPA407/G334A, force range: 0–6000 kgf, frequency range: 0–2500 Hz, ETS Solutions Ltd), DSP (type: MS320F2812, TI Corporation), 12 bit A/D, 16 bit D/A, and data acquisition.
(a) Schematic diagram
(b) Photograph
The acceleration responses of the mass 2 of the vibration control system with different control methods under a 10 Hz sinusoidal, 40 Hz sinusoidal, and nonperiodic acceleration excitations are shown in Figure 10. The uncontrolled method means that the input currents of both the MRD and the MRE are zero.
(a) 10 Hz
(b) 40 Hz
(c) Nonperiodical
The whole evaluation vibration acceleration response is defined as where is the acceleration of the mass 2 in the time .
According to (38) and Figure 10, responses of the vibration control system with different control method are listed in Table 1. The acceleration responses of mass 2 dropped significantly with the semiactive control, which indicates the vibration control system with the semiactive control strategy is very effective in reducing the vibration. Interestingly, the control MRD can effectively reduce the peak acceleration responses but inspire some of the highfrequency vibrations. The MRE can not only marginally reduce the amplitude of the acceleration responses but can also play an important role in highfrequency vibration reduction. Therefore, MREs can be used to make up for the shortcomings of MRDs in vibration control system, which is consistent with the design idea in Section 2.

7. Conclusions and Future Scope
The vibration control system was put forward using the MRD and the MRE connected in series. In order to modeling the hysteresis of the MRD, the BoucWen model and the corresponding parameter identification method were developed for the MRD. The role of the MRE was illustrated by an example of a single degreeoffreedom system. the semiactive vibration control strategy of the proposed vibration control system was proposed. To validate this new approach, experiments were conducted. The following conclusions can be drawn.(1)The experiments results validate the proposed BoucWen model and the corresponding parameter identification method can predict the hysteretic behavior of the MRD accurately.(2)The vibration control system with the semiactive control strategy is very effective in reducing the vibration.(3)The MRD can reduce the largerange and lowfrequency vibration and the MRE can reduce the smallrange and highfrequency vibration.
According to the above conclusions, the future work involves.(1)researching their applications, such as suspension system(2)researching the vibration control system using the MRD and the MRE connected in parallel.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
Acknowledgment
The authors wish to acknowledge the financial support by Natural Science Foundation of China (NSFC Grant no. 61304137).
References
 N. K. Chandiramani and S. P. Purohit, “Semiactive control using magnetorhelogical dampers with output feedback and distributed sensing,” Shock and Vibration, vol. 19, no. 6, pp. 1427–1443, 2012. View at: Publisher Site  Google Scholar
 Y.K. Wen, “Method for random vibration of hysteretic systems,” ASCE Journal of Engineering Mechanics Divison, vol. 102, no. 2, pp. 249–263, 1976. View at: Google Scholar
 B. F. Spencer Jr., S. J. Dyke, M. K. Sain, and J. D. Carlson, “Phenomenological model for magnetorheological dampers,” Journal of Engineering Mechanics, vol. 123, no. 3, pp. 230–238, 1997. View at: Google Scholar
 A. Dominguez, R. Sedaghati, and I. Stiharu, “A new dynamic hysteresis model for magnetorheological dampers,” Smart Materials and Structures, vol. 15, no. 5, pp. 1179–1189, 2006. View at: Publisher Site  Google Scholar
 L. X. Wang and H. Kamath, “Modelling hysteretic behaviour in magnetorheological fluids and dampers using phasetransition theory,” Smart Materials and Structures, vol. 15, no. 6, pp. 1725–1733, 2006. View at: Publisher Site  Google Scholar
 R. Jiménez and L. ÁlvarezIcaza, “LuGre friction model for a magnetorheological damper,” Structural Control and Health Monitoring, vol. 12, no. 1, pp. 91–116, 2005. View at: Publisher Site  Google Scholar
 C. Sakai, H. Ohmori, and A. Sano, “Modeling of MR damper with hysteresis for adaptive vibration control,” in Proceedings of the 42nd IEEE Conference on Decision and Control, pp. 3840–3845, Maui, Hawaii, USA, December 2003. View at: Google Scholar
 Z.D. Xu and Y.P. Shen, “Intelligent bistate control for the structure with magnetorheological dampers,” Journal of Intelligent Material Systems and Structures, vol. 14, no. 1, pp. 35–42, 2003. View at: Publisher Site  Google Scholar
 S. J. Dyke, B. F. Spencer Jr., M. K. Sain, and J. D. Carlson, “Modeling and control of magnetorheological dampers for seismic response reduction,” Smart Materials and Structures, vol. 5, no. 5, pp. 565–575, 1996. View at: Publisher Site  Google Scholar
 S. Frey, K. Groh, and A. Verl, “Semiactive damping of drive systems,” JVC/Journal of Vibration and Control, vol. 19, no. 5, pp. 742–754, 2013. View at: Publisher Site  Google Scholar
 R. S. Prabakar, C. Sujatha, and S. Narayanan, “Optimal semiactive preview control response of a half car vehicle model with magnetorheological damper,” Journal of Sound and Vibration, vol. 326, no. 35, pp. 400–420, 2009. View at: Publisher Site  Google Scholar
 F. Weber, “BoucWen modelbased realtime force tracking scheme for MR dampers,” Smart Materials and Structures, vol. 22, no. 4, Article ID 045012, 12 pages, 2013. View at: Publisher Site  Google Scholar
 G. Y. Zhou and F. Weber, “Complex shear modulus of a magnetorheological elastomer,” Smart Materials and Structures, vol. 13, no. 5, pp. 1203–1210, 2004. View at: Publisher Site  Google Scholar
 Z. Rigbi and L. Jilkén, “The response of an elastomer filled with soft ferrite to mechanical and magnetic influences,” Journal of Magnetism and Magnetic Materials, vol. 37, no. 3, pp. 267–276, 1983. View at: Google Scholar
 M. R. Jolly, J. D. Carlson, and B. C. Muñoz, “A model of the behaviour of magnetorheological materials,” Smart Materials and Structures, vol. 5, no. 5, pp. 607–614, 1996. View at: Publisher Site  Google Scholar
 A. Preuont, Vibration Control of Active Structures, Kluwer Academic Publishers, 2002.
 W. Zhu and D.H. Wang, “Nonsymmetrical BoucWen model for piezoelectric ceramic actuators,” Sensors and Actuators A: Physical, vol. 181, pp. 51–60, 2012. View at: Publisher Site  Google Scholar
 C.J. Lin and S.R. Yang, “Precise positioning of piezoactuated stages using hysteresisobserver based control,” Mechatronics, vol. 16, no. 7, pp. 417–426, 2006. View at: Publisher Site  Google Scholar
 A. Rodríguez, N. Iwata, F. Ikhouane, and J. Rodellar, “Model identification of a largescale magnetorheological fluid damper,” Smart Materials and Structures, vol. 18, no. 1, Article ID 015010, 2009. View at: Publisher Site  Google Scholar
 C. Collette and A. Preumont, “High frequency energy transfer in semiactive suspension,” Journal of Sound and Vibration, vol. 329, no. 22, pp. 4604–4616, 2010. View at: Publisher Site  Google Scholar
 C. Spelta, S. M. Savaresi, F. Codecà, M. Montiglio, and M. Ieluzzi, “Smartbogie: semiactive lateral control of railway vehicles,” Asian Journal of Control, vol. 14, no. 4, pp. 875–890, 2012. View at: Publisher Site  Google Scholar
 F. Weber, “Semiactive vibration absorber based on realtime controlled MR damper,” Mechanical Systems and Signal Processing, vol. 46, pp. 272–288, 2014. View at: Publisher Site  Google Scholar
Copyright
Copyright © 2014 Wei Zhu and Xiaoting Rui. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.