Magnetorheological Elastomer Base Isolator Research Articles

A new hybrid model for MR elastomer device and parameter identification based on improved FOA

A new hysteresis model based on curve fitting method is presented in this work to portray the greatly nonlinear and hysteretic relationships between shear force and displacement responses of the magnetorheological (MR) elastomer base isolator. Compared with classical hysteresis models such as Bouc-Wen or LuGre friction model, the proposed model combines the hyperbolic sine function and Gaussian function to model the hysteretic loops of the device responses, contributing to a great decline of model parameters. Then, an improved fruit fly optimization algorithm (FOA) is proposed to optimize the model parameters, in which a self-adaptive step is employed rather than the fixed step to balance the global and local optimum search abilities of algorithm. Finally, the experimental results of the device under both harmonic and random excitations are used to verify the performance of the proposed hybrid model and parameter identification algorithm with the satisfactory results.

Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

On rate-dependent mechanical model for adaptive magnetorheological elastomer base isolator

This paper presents research on the phenomenological model of an adaptive base isolator. The adaptive base isolator is made of field-dependent magnetorheological elastomer (MRE) which can alter its physical property under application of magnetic field. Experimental testing demonstrated that the developed MRE base isolator possesses an amazing ability to vary its stiffness under applied magnetic field. However, several challenges have been encountered when it comes modeling such novel device. For example, under a large deformation, the MRE base isolator exhibits a clear strain stiffening effect and this behavior escalates with the increasing of applied current. In addition, the MRE base isolator has also shown typical rate-dependent behavior. Following a review on mechanical models for viscos-elastic rubber devices, a novel rate-dependent model is proposed in this paper to capture the behavior of the new MRE base isolator. To develop a generalized model, the proposed model was evaluated using its performance under random displacement input and a seismic input. It shows that the proposed rate-dependent model can successfully describe the complex behavior of the device.

Lyapunov-based Semi-active Control of Adaptive Base Isolation System employing Magnetorheological Elastomer base isolators

One of the main shortcomings in the current passive base isolation system is lack of adaptability. The recent research and development of a novel adaptive seismic isolator based on magnetorheological elastomer (MRE) material has created an opportunity to add adaptability to base isolation systems for civil structures. The new MRE based base isolator is able to significantly alter its shear modulus or lateral stiffness with the applied magnetic field or electric current, which makes it a competitive candidate to develop an adaptive base isolation system. This paper aims at exploring suitable control algorithms for such adaptive base isolation system by developing a close-loop semi-active control system for a building structure equipped with MRE base isolators. The MRE base isolator is simulated by a numerical model derived from experimental characterization based on the Bouc-Wen Model, which is able to describe the forcedisplacement response of the device accurately. The parameters of Bouc-Wen Model such as the stiffness and the damping coefficients are described as functions of the applied current. The state-space model is built by analyzing the dynamic property of the structure embedded with MRE base isolators. A Lyapunov-based controller is designed to adaptively vary the current applied to MRE base isolator to suppress the quakeinduced vibrations. The proposed control method is applied to a widely used benchmark base-isolated structure by numerical simulation. The performance of the adaptive base isolation system was evaluated through comparison with optimal passive base isolation system and a passive base isolation system with optimized base shear. It is concluded that the adaptive base isolation system with proposed Lyapunov-based semi-active control surpasses the performance of other two passive systems in protecting the civil structures under seismic events.

Magnetorheological elastomer base isolator for earthquake response mitigation on building structures: modeling and second-order sliding mode control

Magnetorheological elastomer base isolator for earthquake response mitigation on building structures: modeling and second-order sliding mode control

Nonlinear and Hysteretic Modelling of Magnetorheological Elastomer Base Isolator Using Adaptive Neuro-Fuzzy Inference System

Magnetorheological elastomer (MRE) base isolator is a semi-active control device which has currently obtained increasing attention in the field of vibration control of civil structures. However, the inherent nonlinear and hysteretic response of the device is regarded as a challenge aspect for using the smart device to realize the high performance. Therefore, an accurate and robust model is essential to make full use of these unique features for its engineering applications. In this paper, to solve this issue, adaptive neuro-fuzzy inference system (ANFIS) is utilized to characterize the dynamic behavior of the device. In this proposed model, the inputs are historical displacements and applied current of the device while the output is the shear force generated. To validate its forecast performance, the ANFIS model is also compared with some conventional models. Finally, the result verifies that ANFIS has the best perfection ability among existing MRE-based device models.

Self-adaptive step fruit fly algorithm optimized support vector regression model for dynamic response prediction of magnetorheological elastomer base isolator

Parameter optimization of support vector regression (SVR) plays a challenging role in improving the generalization ability of machine learning. Fruit fly optimization algorithm (FFOA) is a recently developed swarm optimization algorithm for complicated multi-objective optimization problems and is also suitable for optimizing SVR parameters. In this work, parameter optimization in SVR using FFOA is investigated. In view of problems of premature and local optimum in FFOA, an improved FFOA algorithm based on self-adaptive step update strategy (SSFFOA) is presented to obtain the optimal SVR model. Moreover, the proposed method is utilized to characterize magnetorheological elastomer (MRE) base isolator, a typical hysteresis device. In this application, the obtained displacement, velocity and current level are used as SVR inputs while the output is the shear force response of the device. Experimental testing of the isolator with two types of excitations is applied for model performance evaluation. The results demonstrate that the proposed SSFFOA-optimized SVR (SSFFOA_SVR) has perfect generalization ability and more accurate prediction accuracy than other machine learning models, and it is a suitable and effective method to predict the dynamic behaviour of MRE isolator.

A hysteresis model for dynamic behaviour of magnetorheological elastomer base isolator

In recent years, an adaptively tuned magnetorheological elastomer (MRE) isolator for a base isolation system has been designed and tested with the benefits of low power cost, fail safe manner and fast responses. To make full use of this striking device for design of smart structures, a highly precise model should be developed to effectively and accurately forecast the shear force of the device in real-time so as to adopt a proper control strategy to improve the responses of the protected structures. In this work, a novel mechanical model is presented to characterize this nonlinear hysteresis for its implementation in structural vibration control. This model employs the displacement and velocity of the device as well as the applied current as the inputs and just has the limited constant parameters to be identified compared with some classical hysteretic models such as Bouc–Wen, improved Dahl and LuGre models. Performance evaluation of this novel hysteresis model has been conducted based on the testing data from an MRE base isolator. The results show that the proposed model has high modelling accuracy and is able to perfectly portray the unique and complicated behaviours of the device with various excitations.

Frequency control of smart base isolation system employing a novel adaptive magneto-rheological elastomer base isolator

In the past decades, base isolation techniques have become increasingly popular for seismic protection of civil structures owing to its capability of decoupling buildings from harmful ground motion. However, it has been recognised recently that the traditional passive base isolation technique could encounter a serious problem during earthquakes due its incapability in adjusting the isolation frequency to cope with the unpredictability and diversity of earthquakes. To address this challenge, a great deal of research efforts have been conducted to improve traditional base isolation systems, most of which focused on hybrid supplementary devices (passive, active and semi-active types) for the isolators to control displacement or to dissipate seismic energy. On the other hand, the most effective approach to address the aforementioned challenge should lay on varying isolator stiffness in real-time to achieve real-time spontaneous decoupling. A recent advance of the development of an adaptive magneto-rheological elastomer base isolator has brought such idea to reality as the new magneto-rheological elastomer base isolator is capable to alter its stiffness significantly in real-time. In this article, an innovative smart base isolation system employing such magneto-rheological elastomer isolator is proposed and a novel frequency control algorithm is developed to shift the fundamental frequency of the structure away from the dominant frequency range of earthquakes. Such design enables the building to avoid resonant state in real-time according to the on-coming spectrum of the earthquakes. Extensive simulation has been conducted using a five-storey benchmark model with the isolation system, and testing results indicate that the proposed control system is able to significantly suppress both the floor accelerations and inter-storey drifts simultaneously under different earthquakes.

Parameter identification and sensitivity analysis of an improved LuGre friction model for magnetorheological elastomer base isolator

The recently-developed magnetorheological elastomer (MRE) base isolator can provide an instant change in the shear modulus and damping property under applied magnetic field, which makes it as an ideal device for the semi-active control in buildings and bridges. Previous studies show that this new device is featured with its nonlinear and hysteretic responses, and it is necessary to sufficiently understand its behaviour when adopting this device in control system. Although there are several models presented to predict the hysteresis of MRE base isolator, they are always suffered from some application limitations, e.g. high computation demand or complex model. To better interpret this complicated feature of the device, this work presents an improved LuGre friction model, which has been successfully used in modelling other magnetorheological device i.e. MR damper. In addition, an improved fruit fly optimization algorithm (IFFOA) is also proposed to identify the model parameters. In the improved algorithm, a transfer factor based on a self-adaptive step is added together with a three-dimensional searching space. This improvement can enhance the convergence rate of the algorithm and avoid the local optimum. Furthermore, to reduce the complexity of the model, the local and global parameter sensitivity analyses are conducted for model simplification. Eventually, the experimental measurements of device displacement, velocity and shear force are used to evaluate the performance of the proposed model and IFFOA.

Finite element design and analysis of adaptive base isolator utilizing laminated multiple magnetorheological elastomer layers

Available magnetorheological elastomer devices normally consist one to two layers of small-size magnetorheological elastomer materials. To be used in large-scale structures, magnetorheological elastomer devices with multiple larger magnetorheological elastomer materials are expected. This article addresses the critical issue in designing a large-scale device with multiple layers of low magnetic conductive magnetorheological elastomer materials, that is, magnetic circuit design. The primary target in magnetic circuit design for magnetorheological elastomer devices is to provide sufficient and uniform magnetic field to all magnetorheological elastomer layers in the device. In this article, finite element investigations are conducted. An innovative magnetic circuit design is proposed for magnetorheological elastomer base isolator with multi-layer of magnetorheological elastomer materials. In the design, laminated magnetorheological elastomer and steel structure is adopted as part of the magnetic core together with two steel blocks. Cylindrical steel tube is used as the yoke of the magnetic circuit. Two plates are placed on the top and bottom of the device to form enclosed magnetic path in the device. Finite element results showed that such innovative magnetic design is able to provide sufficient and uniform magnetic field to all magnetorheological elastomer layers, that is, 25 magnetorheological elastomer layers with thickness of 1 mm and diameter of 120 mm in this case. Finally, the influence of lateral deformation of the magnetorheological elastomer base isolator on the magnetic field is investigated. It is found that the magnetic field in magnetorheological elastomer materials deteriorates when the deformation of the device increases.

Nonparametric modeling of magnetorheological elastomer base isolator based on artificial neural network optimized by ant colony algorithm

Laminated magnetorheological elastomer base isolator is regarded as one of the most promising candidates for realizing adaptive base isolation for civil structures. However, the intrinsic hysteretic and nonlinear behavior of magnetorheological elastomer base isolators imposes challenge for adopting the device to accomplish high-accuracy performance in structural control. Therefore, it is essential to develop an accurate model for symbolizing this unique characteristic before designing a feedback controller. So far, some classical parametric models, such as Bouc–Wen, Dahl, and LuGre, have been proposed to depict the hysteretic response of magnetorheological devices, that is, magnetorheological damper, which may also be used for describing the nonlinear behavior of magnetorheological elastomer base isolator. However, the parameter identification is difficult to implement due to the nonlinear differential equations existing in these models. Considering this problem, this article proposes a nonparametric model, that is, an artificial neural network–based model with 3 input neurons, 18 hidden neurons, and 1 output neuron, to predict the magnetorheological elastomer isolator behavior. In this model, the ant colony algorithm is employed for model training to obtain the optimal weights based on the force–displacement/velocity data sampled from the magnetorheological elastomer isolator. Finally, experimental data are used to validate the effectiveness of the proposed artificial neural network–based model with the good forecasting results.

Forecasting hysteresis behaviours of magnetorheological elastomer base isolator utilizing a hybrid model based on support vector regression and improved particle swarm optimization

Due to its inherent hysteretic characteristics, the main challenge for the application of a magnetorheological elastomer- (MRE) based isolator is the exploitation of the accurate model, which could fully describe its unique behaviour. This paper proposes a nonparametric model for a MRE-based isolator based on support vector regression (SVR). The trained identification model is to forecast the shear force of the MRE-based isolator online; thus, the dynamic response from the MRE-based isolator can be well captured. In order to improve the forecast capacity of the model, a type of improved particle swarm optimization (IPSO) is employed to optimize the parameters in SVR. Eventually, the trained model is applied to the MRE-based isolator modelling with testing data. The results indicate that the proposed hybrid model has a better generalization capacity and better recognition accuracy than other conventional models, and it is an effective and suitable approach for forecasting the behaviours of a MRE-based isolator.

A Highly Adjustable Base Isolator Utilizing Magnetorheological Elastomer: Experimental Testing and Modeling

This paper presents a recent research advance on the development of a novel adaptive seismic isolation system to be used in seismic protection of civil structures. A highly adjustable laminated magnetorheological elastomer (MRE) base isolator was developed and experimental results show that the prototypical MRE base isolator provides increase in lateral stiffness up to 1630%. To facilitate the structural control development using such adaptive MRE base isolator, an analytical model was developed to simulate its behaviors. Comparison between the analytical model and experimental data proves the effectiveness of such model in reproducing the behavior of MRE base isolator.

Parameter identification of a novel strain stiffening model for magnetorheological elastomer base isolator utilizing enhanced particle swarm optimization

This article presents a novel model to describe the nonlinear relationships between shear force and displacement/velocity in a magnetorheological elastomer base isolator. The proposed model, containing a strain stiffening element, is able to portray the distinct dynamic behaviors of magnetorheological elastomer base isolator. To identify the model parameters, an enhanced particle swarm optimization is used on force–displacement/velocity data sampled under different loading conditions. In this algorithm, a self-adaptive inertia weight replaces the general linear weight, enhancing the convergence rate of iteration process. Besides, the mutation operator in genetic algorithm is adopted for finding global optimum. Testing data of the device displacement, velocity and force from magnetorheological elastomer base isolator are utilized to validate the proposed model and corresponding parameter identification algorithm.

Modeling of a new semi-active/passive magnetorheological elastomer isolator

This paper presents theoretical modeling of a new magnetorheological elastomer (MRE) base isolator and its performance for vibration control. The elastomeric element of the traditional steel–rubber base isolator is modified to a composite layer of passive elastomer and MRE which makes the isolator controllable with respect to its stiffness and damping. The proposed variable stiffness and damping isolator (VSDI) is designed based on an optimized magnetic field passing through MRE layers to achieve maximum changes in mechanical properties. The controllability of the VSDI is investigated experimentally under double lap shear tests. A model employing the Bouc–Wen hysteresis element is proposed to characterize the force–displacement relationship of the VSDI. An integrated system which consists of four VSDIs is designed, built and tested. Dynamic testing on the integrated system is performed to investigate the effectiveness of the VSDIs for vibration control. Experimental results show significant shift in natural frequency, when VSDIs are activated and the possibility of using the VSDIs as a controllable base isolator.

A highly adjustable magnetorheological elastomer base isolator for applications of real-time adaptive control

Inspired by its controllable and field-dependent stiffness/damping properties, there has been increasing research and development of magnetorheological elastomer (MRE) for mitigation of unwanted structural or machinery vibrations using MRE isolators or absorbers. Recently, a breakthrough pilot research on the development of a highly innovative prototype adaptive MRE base isolator, with the ability for real-time adaptive control of base isolated structures against various types of earthquakes including near- or far-fault earthquakes, has been reported by the authors. As a further effort to improve the proposed MRE adaptive base isolator and to address some of the shortcomings and challenges, this paper presents systematic investigations on the development of a new highly adjustable MRE base isolator, including experimental testing and characterization of the new isolator. A soft MR elastomer has been designed, fabricated and incorporated in the laminated structure of the new MRE base isolator, which aims to obtain a highly adjustable shear modulus under a medium level of magnetic field. Comprehensive static and dynamic testing was conducted on this new adaptive MRE base isolator to examine its characteristics and evaluate its performance. The experimental results show that this new MRE base isolator can remarkably change the lateral stiffness of the isolator up to 1630% under a medium level of magnetic field. Such highly adjustable MRE base isolator makes the design and implementation of truly real-time adaptive (e.g. semi-active or smart passive) seismic isolation systems become feasible.

On the magnetic field and temperature monitoring of a solenoid coil for a novel magnetorheological elastomer base isolator

Following a successful experimental validation of a magnetorheological elastomer (MRE) base isolator, this study presents one of the major concerns, the heating of the magnetic coil, in the design and development of the adaptive MRE based isolator. In this research, the MRE materials, with a total thickness of nearly 150 mm, are placed as the magnetic core of the device to best utilize the magnetic energy provided by the coil. A series of tests are undertaken to investigate the magnetic fields inside the coil with or without the MRE materials. Thermocouples are used to monitoring the surface temperature of the coil when it is applied with various currents for 10 min. It is shown that the measurement of field inside the solenoid when no MRE is placed inside agrees with the theoretical analysis. It is also shown that the temperature of the coil increase dramatically when a current is applied. Cooling of the coil may takes even longer, about 4 h, till down to the room temperature. Dropping of the magnetic field is observed when the temperature goes high.