Semi-active control of structures incorporated with magnetorheological dampers using neural networks

Xu, Zhao‐Dong; Shen, Yuhui; Guo, Yingqing

doi:10.1088/0964-1726/12/1/309

Cited by 163 publications

(109 citation statements)

References 20 publications

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“…Lord Corporation 4 used MR dampers for the vibration control of armored vehicles. Xu et al 5 used the MR damper for mitigating earthquake responses of building structure under the neural networks control strategy.…”

Section: Introductionmentioning

confidence: 99%

Preparation and Experimental Study of Magnetorheological Fluids for Vibration Control

Guo¹,

Xu²,

Chen³

et al. 2017

IJAV

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Magnetorheological (MR) fluids are a new kind of smart vibration mitigation material for vibration control, whose shear yield stress can change in magnetic field, and the change can occur only in a few milliseconds. The rheological properties, anti-settlement stability, and redispersibility are the very important properties of MR fluids. In this paper, a kind of preparation process of MR fluids is introduced and MR fluids with different grain diameter ratios of carbonyl iron particles are produced. Then, the properties of self-prepared MR fluids are tested, including the sedimentation stability test, viscosity test, and shear yield stress test. The results of the MR fluid property tests show that the adding of 10 µm-carbonyl iron particles will improve the magnetic effect of MR fluids, increase the zero magnetic field viscosity of MR fluids, and increase shear yield stress of MR fluids in same magnetic field, but the anti-settlement properties will be degraded.

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Section: Introductionmentioning

confidence: 99%

Preparation and Experimental Study of Magnetorheological Fluids for Vibration Control

Guo¹,

Xu²,

Chen³

et al. 2017

IJAV

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“…Among such algorithms, those based on artificial neural networks (ANNs) and fuzzy logic stand out. Neural network-based controllers were employed in [16][17][18][19][20]. These algorithms generally operate as predictive models, where the main objective is to determine the actions to be executed by energy-dissipating devices to reduce the system's response to dynamic actions.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of semi-active control algorithms applied to magnetorheological dampers

Lara-V.

Brito²,

2017

Ingeniare. Rev. chil. ing.

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This paper analyzes the performance of three different semi-active control algorithms used to calculate and manage the optimal damping forces generated by a pair of magnetorheological (MR) dampers installed in a two-story building. The semi-active algorithms used are the linear quadratic regulator (LQR) associated with the clipped optimal algorithm, an algorithm based on a prediction model and a dynamic inverse model using nonlinear autoregressive exogenous (NARX)-type artificial neural networks, and a decision-making algorithm based on fuzzy logic. Additionally, the performances of the proposed semi-active algorithms are compared to those of passively used control devices. The results show response value reductions exceeding 50% for all the semi-active control strategies, which considerably outperformed the passive control. The three control strategies are thus confirmed as interesting tools with potential applications as MR damper administrators.Keywords: Structure dynamics, semi-active control of structures, vibration reduction, magnetorheological dampers, control algorithms, intelligent systems. RESUMEN En este artículo se analiza numéricamente la eficiencia y el desempeño de tres diferentes algoritmos de control semiactivo que tienen la función de calcular y administrar las fuerzas óptimas de amortiguamiento que deben ser generadas por un par de amortiguadores magnetoreológicos instalados en una estructura de dos niveles. Los algoritmos semi-activos empleados son el regulador lineal cuadrático (LQR), asociado al algoritmo clipped optimal y dos algoritmos fundamentados en sistemas inteligentes: un algoritmo basado en un modelo de predicción y en un modelo inverso dinámico construidos por medio de redes neuronales artificiales de tipo NARX y un algoritmo de toma de decisiones basados en lógica difusa. Adicionalmente, la actuación de los algoritmos de control semi-activo propuestos es comparada con el desempeño de los

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“…al. [21] consider the Semi-active control of buildings and structures with magnetorheological (MR) dampers where they utilized the Bingham model of MR damper. In their note they proposed a novel real-time control method of vibrations based on neural-network model of the system.…”

Section: Introductionmentioning

confidence: 99%

Active Vibration Control of Container Cranes against Earthquake by the Use of Delay-Dependent H_∞ Controller under Consideration of Actuator Saturation

Yazıcı

Azeloglu

Küçükdemiral

2014

Journal of Low Frequency Noise, Vibration and Active Control

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This paper studies the design of a state-feedback delay-dependent H ∞ controller for vibration attenuation problem of a seismic-excited container crane subject to having time-varying actuator delay, L 2 type disturbances and actuator saturation. First, a sufficient delay-dependent stability criterion is developed by choosing a Lyapunov-Krasovskii functional candidate based on matrix inequalities for a stabilizing H ∞ synthesis. To convexify the Bilinear Matrix Inequality (BMI) based optimization problem involved in the delay dependent conditions; a cone complementary linearization method is adopted to find a sub-optimal solution. The proposed method also utilizes convex description of nonlinear saturation phenomenon by means of convex hull of some linear feedback which leads to a few additional ellipsoidal conditions in terms of Linear Matrix Inequalities (LMIs). By use of the proposed method, a suboptimal controller with maximum allowable delay bound and minimum allowable disturbance attenuation level can be easily obtained by a convex optimization technique. In order to show effectiveness of the proposed approach, a five Degrees-of-Freedom (DOF) container crane structure is modeled using a spring-mass-damper subsystem. The system is then simulated against the real ground motions of Kobe and Northridge earthquakes. Finally, the time history of the crane parts displacements, accelerations, control forces and frequency responses of the both uncontrolled and controlled cases are presented. Additionally, the performance of the proposed controller is also compared with a nominal state-feedback H ∞ controller performance. Simulation results show that, in spite of the actuator saturation, the designed controller is all effective in reducing vibration amplitudes of crane parts and guarantees stability at maximum actuator delay.

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Semi-active control of structures incorporated with magnetorheological dampers using neural networks

Cited by 163 publications

References 20 publications

Preparation and Experimental Study of Magnetorheological Fluids for Vibration Control

Preparation and Experimental Study of Magnetorheological Fluids for Vibration Control

Comparative analysis of semi-active control algorithms applied to magnetorheological dampers

Active Vibration Control of Container Cranes against Earthquake by the Use of Delay-Dependent H_∞ Controller under Consideration of Actuator Saturation

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Semi-active control of structures incorporated with magnetorheological dampers using neural networks

Cited by 163 publications

References 20 publications

Preparation and Experimental Study of Magnetorheological Fluids for Vibration Control

Preparation and Experimental Study of Magnetorheological Fluids for Vibration Control

Comparative analysis of semi-active control algorithms applied to magnetorheological dampers

Active Vibration Control of Container Cranes against Earthquake by the Use of Delay-Dependent H∞ Controller under Consideration of Actuator Saturation

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Active Vibration Control of Container Cranes against Earthquake by the Use of Delay-Dependent H_∞ Controller under Consideration of Actuator Saturation