Optimal vibration control for nonlinear systems of tracked vehicle half-car suspensions

Liang, Yanjun; Li, Na; Gao, De-Xin; Wang, Zhongsheng

doi:10.1007/s12555-015-0447-7

Cited by 15 publications

(8 citation statements)

References 16 publications

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“…A mathematical model of the new suspension system was built, and experiments were held to verify the model. Liang et al [23] proposed an optimal control approach to elongate the suspension system life and to improve ride comfort. A nonlinear dynamic model was established and simulated for half-car suspension.…”

Section: Introductionmentioning

confidence: 99%

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

et al. 2021

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One type of vehicle suspension system is the air suspension system. One of the important functions of the suspension system is to reduce vibration transmitted to the vehicle body from road unevenness. Soft suspension results in better ride comfort and worst handling. While stiff suspension results in better handling and worse comfort. This paper investigates the performance of air suspension in terms of passenger ride comfort and vehicle handling. The performance is tested once with Fuzzy logic control and another with Fuzzy control augmented with Neuro-Fuzzy inference system. A mathematical model is developed to describe the air-spring stiffness behavior. The air-spring suspension is merged on two degrees of freedom model. The air pressure is controlled by a Fuzzy controller as done previously in the literature. On the other hand, our approach is to control the volume change by connecting the air-spring volume to two additional unequal volumes through ON-OFF solenoid valves. The solenoid valves are controlled by Adaptive Neuro-Fuzzy Inference System (ANFIS). A single-degree-of-freedom setup was built from which the required training data for the ANFIS controller was carried out. The experimental setup is developed with variable excitation input in terms of frequency and amplitudes. The acceleration of the sprung mass has been measured and stored at different operating conditions and including different air volumes. The stored data is used for training of volume controller. The controller is tested with Sinusoidal excitation then with ISO 8608 road profile. It is found that increasing the air volume reduces the sprung mass acceleration. Also, the results showed that implementing the Neuro-Fuzzy controller with Fuzzy logic control reduces the sprung mass acceleration significantly by an average value that reaches 5 cm/s 2 at frequencies above 1 Hz while maintaining road holding.

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Section: Introductionmentioning

confidence: 99%

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

et al. 2021

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“…Nazemian et al [12] developed an optimized controller to maximize the dynamic performance and reduce the energy assumption of the pneumatic suspension. Some adaptive sliding mode controllers were proposed to address the unknown dynamics of the pneumatic suspension [13], [14]. Rui et al [15] designed an adaptive sliding mode control considering the nonlinear dynamical characteristic of the pneumatic system.…”

Section: Introductionmentioning

confidence: 99%

Design of an Adaptive Fuzzy Observer-Based Fault Tolerant Controller for Pneumatic Active Suspension With Displacement Constraint

Ahn²

2021

IEEE Access

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This paper proposes an adaptive fuzzy observer based fault tolerant controller for a pneumatic active suspension system considering unknown parameters, actuator failures, and displacement constraints. A pneumatic spring is used for a quarter car model to enhance the vibration attenuation performance. Since the pneumatic system contains uncertain nonlinearities, fuzzy logic systems are utilized to approximate unknown nonlinear functions of unmodeled dynamics and various masses of passengers. Besides, a nonlinear disturbance observer is proposed to estimate the effects of the actuator failures, approximation errors, and external disturbances. By utilizing the disturbance estimation and fuzzy approximation techniques, an adaptive fault tolerant control (FTC) is designed to enhance the output performance of the vehicle suspension. Meanwhile, the command filtered scheme is introduced to solve the explosion of complexity problem in the traditional backstepping approach by avoiding virtual controller derivatives. In contrast to previous results, the proposed control can handle the fault tolerant problem and ensure the tracking error of vertical displacement converges into a small-predefined boundary by introducing the prescribed performance function. Moreover, the stability of the closed-loop system is analyzed according to the Lyapunov theory. Finally, comparative simulation examples and experimental studies are performed on the active pneumatic suspension test bench to verify the feasibility of the proposed scheme.INDEX TERMS Active suspension systems (ASSs), nonlinear disturbance observer (NDOB), prescribed performance function (PPF), fuzzy logic systems (FLSs), command filtered control (CFC).

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“…Yıldız et al [28] developed a nonlinear model of the damper to predict the damping force based on voltage input, internal state and velocity input. Liang et al [29] established a nonlinear systems of tracked vehicle half-car suspensions considering the nonlinear damping of springs. Kilicaslan [30] develop a suspension system considering nonlinear actuator dynamics for active suspension control.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Nonlinear Stiffness of Novel Flexible Road Wheel on Ride Comfort of Tracked Vehicle Traversing Random Uneven Road

Deng

Zhao

et al. 2019

IEEE Access

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The linear wheel model is the most widely used in ride comfort analysis of tracked vehicles. However, as the speed of the vehicle increases and the application of new materials, and the road wheel becomes lighter and softer, its nonlinear characteristics become more and more obvious and can't be ignored in vehicle dynamics simulation. This paper aims to study the effect of nonlinear stiffness of a novel flexible road wheel (FRW) with unique suspension bearing structure on the ride comfort of a tracked vehicle traversing random uneven road. The linear and nonlinear models of FRW were established by fitting the load-deflection data obtained from the static loading test of the physical prototype. The established linear and nonlinear models of FRW were added to a half-vehicle model of a tracked vehicle which has been proved by published test results. The ride comfort of the half-vehicle model of the tracked vehicle with linear and nonlinear models of FRW on random uneven road surface was studied in detail. The study results show that, compared with the linear wheel model, the nonlinear model has a tremendous influence on the dynamic response of the tracked vehicle, effectively suppressing the vibration, especially for the high frequency excitation. In addition, the nonlinear factor has a greater impact on the dynamic performance of the wheel than on the suspension and the body. The research results enrich the study of nonlinear dynamics of tracked vehicles, and provide reference for nonlinear modeling of other pneumatic tires and non-inflatable wheels.INDEX TERMS Ride comfort, flexible road wheel, wheel stiffness test, nonlinear wheel model, Matlab/Simulink.

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Optimal vibration control for nonlinear systems of tracked vehicle half-car suspensions

Cited by 15 publications

References 16 publications

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

Neuro-Fuzzy Volume Control for Quarter Car Air-Spring Suspension System

Design of an Adaptive Fuzzy Observer-Based Fault Tolerant Controller for Pneumatic Active Suspension With Displacement Constraint

The Influence of Nonlinear Stiffness of Novel Flexible Road Wheel on Ride Comfort of Tracked Vehicle Traversing Random Uneven Road

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