Intelligent semi-active vibration control of eleven degrees of freedom suspension system using magnetorheological dampers

Zareh, Seiyed Hamid; Sarrafan, Atabak; Khayyat, Amir Ali Akbar; Zabihollah, Abolghassem

doi:10.1007/s12206-011-1007-6

Cited by 32 publications

(22 citation statements)

References 15 publications

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“…The model of the vehicle is taken from [37] and includes the dynamics of the seats, the wheels, and the suspension system. In order to measure the amount of vibration transmitted by the vehicle, it is assumed that the left wheels of the vehicle are moving on a series of two bumps with constant speed, see [37] for further details on the vehicle model.…”

Section: A Vibration Transmitted By a Vehicle Suspension Systemmentioning

confidence: 99%

Log-Sum-Exp Neural Networks and Posynomial Models for Convex and Log-Log-Convex Data

Calafiore

Gaubert

Possieri

2020

IEEE Trans. Neural Netw. Learning Syst.

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We show in this paper that a one-layer feedforward neural network with exponential activation functions in the inner layer and logarithmic activation in the output neuron is an universal approximator of convex functions. Such a network represents a family of scaled log-sum exponential functions, here named LSET . Under a suitable exponential transformation, the class of LSET functions maps to a family of generalized posynomials GPOST , which we similarly show to be universal approximators for log-log-convex functions.A key feature of an LSET network is that, once it is trained on data, the resulting model is convex in the variables, which makes it readily amenable to efficient design based on convex optimization. Similarly, once a GPOST model is trained on data, it yields a posynomial model that can be efficiently optimized with respect to its variables by using geometric programming (GP).The proposed methodology is illustrated by two numerical examples, in which, first, models are constructed from simulation data of the two physical processes (namely, the level of vibration in a vehicle suspension system, and the peak power generated by the combustion of propane), and then optimization-based design is performed on these models.

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Section: A Vibration Transmitted By a Vehicle Suspension Systemmentioning

confidence: 99%

Log-Sum-Exp Neural Networks and Posynomial Models for Convex and Log-Log-Convex Data

Calafiore

Gaubert

Possieri

2020

IEEE Trans. Neural Netw. Learning Syst.

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“…Unsal et al (2008) proposed a 6-DOF parallel platform model for which each leg is modeled as a 2-DOF system with a coil-over MR damper to adjust damping and an actuator for positioning, and it provides effective vibration isolation performance and precise positioning capability with reduced cost and reduced power requirements. Zareh et al (2012) proposed an 11-DOF passenger car's suspension system which uses MR dampers with neuro-fuzzy (NF) control strategy as well as a novel intelligent semi-active control system. The inverse mapping model is proposed to estimate the force needed for a semi-active damper.…”

Section: Intelligent Control Devicesmentioning

confidence: 99%

Recent Advances in Multi-Dimensional Vibration Mitigation Materials and Devices

Chen

Zhou

et al. 2019

Front. Mater.

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Harmful vibrations can cause many engineering problems, such as disasters of civil engineering structures, failure of precision equipment, and the disruption of some spacecraft components. In most situations, the vibrations are usually three-dimensional excitations. Therefore, research on multi-dimensional vibration control has become a worldwide hotspot in engineering. This article presents a comprehensive assessment of recent developments of multi-dimensional vibration mitigation devices and the material applied in such devices. The vibration mitigation materials mainly include the passive vibration mitigation materials and smart vibration mitigation materials. Subsequently, the vibration mitigation devices in civil engineering, mechanical engineering, and aerospace engineering are reviewed and commented, respectively. Above all, the multi-dimensional vibration mitigation devices and materials are found to be effective for reducing multi-dimensional vibrations. However, enhancing the mitigation performance of the devices in each direction, including improving the mitigation capability of materials, is still a challenging issue.

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“…10 The application of GPS system into MR/pneumatic suspension control is proposed by Morales, achieved the same roll angle levels as in a comparable passive vehicle while improving ride comfort by reducing accelerations up to 30%. 11 The control strategies commonly used for semi-active suspension include optimal control, 10,[12][13][14] skyhook control, 15,16 sliding mode control, 17,18 fuzzy control, 19,20 and PID control, 21,22 etc. Skyhook control and sliding mode control exhibit certain robustness, but they are not designed to realize the optimal system performance.…”

Section: Introductionmentioning

confidence: 99%

Investigation on linear quadratic Gaussian control of semi-active suspension for three-axle vehicle

Zhao

Zhang

2020

Journal of Low Frequency Noise, Vibration and Active Control

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An 8-DOF three-axle vehicle model with semi-active suspension is built in this paper, of which the accuracy is verified through simulations and experiments. Based on the optimal control theory, the linear quadratic Gaussian controller for semi-active suspension is designed with 10 evaluation indicators. Considering the deficiency of linear quadratic Gaussian control weight coefficients based on experience, analytic hierarchy process is employed to determine the weight coefficients of each indicator. The control effect is analyzed through MATLAB/Simulink. The adaptability of proposed control strategy under 25 driving conditions is analyzed with different road grades and speeds. The driving condition of “70 km/h travel speed on the road of grade B” is selected, under which the comparison of vehicle responses between semi-active suspension and passive suspension is made. Results show that the vertical vibration is effectively diminished by using semi-active suspension with linear quadratic Gaussian controller. Compared with passive suspension, the riding comfort is improved and the adverse effect on handling stability is eliminated. The three-axle vehicle with semi-active suspension has good adaptability to various working conditions.

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Intelligent semi-active vibration control of eleven degrees of freedom suspension system using magnetorheological dampers

Cited by 32 publications

References 15 publications

Log-Sum-Exp Neural Networks and Posynomial Models for Convex and Log-Log-Convex Data

Log-Sum-Exp Neural Networks and Posynomial Models for Convex and Log-Log-Convex Data

Recent Advances in Multi-Dimensional Vibration Mitigation Materials and Devices

Investigation on linear quadratic Gaussian control of semi-active suspension for three-axle vehicle

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