Inverse neuro-fuzzy MR damper model and its application in vibration control of vehicle suspension system

Zong, Luhang; Gong, Xinglong; Guo, Chaoyang; Xuan, Shouhu

doi:10.1080/00423114.2011.645489

Cited by 67 publications

(60 citation statements)

References 18 publications

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“…This model can accurately capture both the force-displacement and force-velocity hysteresis loops, which involve as many as 14 parameters. In contrast, Kamath and Wereley [120] developed an augmented six-parameter model to accurately describe both the force-displacement and force-velocity hysteresis cycles, which was constructed using a nonlinear combination of linear mechanisms. Choi and Lee [83] proposed the damper model shown in Fig.…”

Section: Dampersmentioning

confidence: 97%

See 1 more Smart Citation

Physical characteristics of magnetorheological suspensions and their applications

Bîcă¹,

Liu²,

Choi³

2013

Journal of Industrial and Engineering Chemistry

174

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Section: Dampersmentioning

confidence: 97%

“…Several models were proposed to characterize the performance of the MR damper [82,119,120]. Spencer et al [121] proposed a modified Bouc-Wen model to describe the MR damper behavior.…”

Section: Dampersmentioning

confidence: 99%

Physical characteristics of magnetorheological suspensions and their applications

Bîcă¹,

Liu²,

Choi³

2013

Journal of Industrial and Engineering Chemistry

174

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“…Simulation results showed that the vibration reduction performance of self-tuning fuzzy logic controller is best compared to uncontrolled and Fuzzy Logic controlled suspension systems. Recently, many control strategies have been developed and evaluated for their practical applicability in semi-active suspension system, which includes H-infinity control [18], fuzzy hybrids [19], hybrid sliding mode control [20], LQG control [21] and adaptive neuro fuzzy hybrid control [22], etc.…”

Section: Introductionmentioning

confidence: 99%

Passenger seat vibration control of a semi-active quarter car system with hybrid Fuzzy–PID approach

Singh

Aggarwal

2015

Int. J. Dynam. Control

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In this paper, semi-active quarter car system with three degrees of freedom is considered for modeling and evaluation of passenger ride comfort. Experimental results of magneto-rheological shock absorber are modeled using polynomial model. The considered algorithms in semi-active quarter car suspension system include PID controller, fuzzy logic controller, hybrid fuzzy-PID controller and hybrid fuzzy-PID controller with coupled rules. Simulation responses of the controlled semi-active and uncontrolled quarter car systems are compared under bump type of road excitation in time domain. Simulation results demonstrate that the semi-active suspension system having hybrid fuzzy-PID controller with coupled rules provide best performance in controlling the passenger seat acceleration and displacement response compared to uncontrolled and other controlled cases.

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“…Neural networks (NN) have been effectively applied to model complex systems due to their good learning capability. Zong et al (2012) propose an adaptive neuro-fuzzy inference system (ANFIS) inverse model to determine the input current so as to gain the desired damping force. Simulation results demonstrate that the desired force can be accurately tracked using the ANFIS technique.…”

Section: Introductionmentioning

confidence: 99%

A novel inverse dynamic model for a magnetorheological damper based on network inversion

Boada

Díaz

2017

Journal of Vibration and Control

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Semi-active suspensions based on magnetorheological (MR) dampers are receiving significant attention specially for control of vibration isolation systems. The nonlinear hysteretic behaviour of MR dampers can cause serious problems in controlled systems such as instability and loss of robustness. Most of the developed controllers determine the desired damping forces which should be produced by the MR damper. Nevertheless, the MR damper behaviour can only be controlled in terms of the applied current (or voltage). In addition to this, it is necessary to develop an adequate inverse dynamic model in order to calculate the command current (or voltage) for the MR damper to generate the desired forces as close as possible to the optimal ones. Due to MR dampers are highly nonlinear devices, the inverse dynamics model is difficult to obtain. In this paper, a novel inverse MR damper model based on a network inversion to estimate the necessary current (or voltage) such as the desired force is exerted by the MR damper is presented. The proposed inverse model is validated carrying out experimental tests. In addition, a comparison of simulated tests with other damper controllers is also presented. Results show the effectiveness of the network inversion for inverse modeling of an MR damper, so that the proposed inverse model can act as a damper controller to generate the command current (or voltage) to track the desired damping force. Keywords

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Inverse neuro-fuzzy MR damper model and its application in vibration control of vehicle suspension system

Cited by 67 publications

References 18 publications

Physical characteristics of magnetorheological suspensions and their applications

Physical characteristics of magnetorheological suspensions and their applications

Passenger seat vibration control of a semi-active quarter car system with hybrid Fuzzy–PID approach

A novel inverse dynamic model for a magnetorheological damper based on network inversion

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