Fractional-order sliding-mode controller for semi-active vehicle MRD suspensions

Nguyen, Sy Dzung; Hoa, Ngo Van

doi:10.1007/s11071-020-05818-w

Cited by 28 publications

(11 citation statements)

References 52 publications

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“…The system obtained high performance control under uncertainty and external disturbance. 25 Sathishkumar used a fuzzy control strategy to actively control the 3-DOF air suspension system model of 1/4 vehicle. 26 In order to analyze the performance of the active suspension system, the seat and body acceleration were selected to judge the state of the control system.…”

Section: Current Status Of Air Suspension Researchmentioning

confidence: 99%

Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system

Wang

et al. 2021

Journal of Low Frequency Noise, Vibration and Active Control

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To improve the ride comfort of wheeled armored vehicles, air springs are used. To describe the vehicle motion more accurately, a nine-degree-of-freedom air suspension system for the whole vehicle was established, and its equations of motion were derived. Through theoretical analysis of the stiffness characteristics and forces on the air springs, the nonlinear restoring force was obtained as a cubic polynomial of the air spring displacement. The simulation results obtained by fitting the polynomial and radial basis function curves with MATLAB/Simulink software are consistent with the actual test results, thus verifying the correctness of the nonlinear air spring polynomial model. Finally, a fuzzy fractional order PIλDμ controller is designed and simulated for the vehicle-seat-body model in terms of wheel dynamic load, suspension dynamic deflection, body acceleration, and other indicators. The simulation results show that the fuzzy fractional order PIλDμ Proportion Integral Differential (PID) control strategy has better overall performance than the PID control strategy, fuzzy control strategy, and fuzzy PID control strategy.

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Section: Current Status Of Air Suspension Researchmentioning

confidence: 99%

Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system

Wang

et al. 2021

Journal of Low Frequency Noise, Vibration and Active Control

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“…The suspension system is the transmission device connecting the wheels and the car body, which mainly undertakes the body mass and ensures good contact between the tire and the ground, as well as reducing the uneven excitation from the road surface [1]. Compared with the traditional suspension system, the air spring suspension system has the advantages of being light weight, being low noise and having favorable vibration isolation performance.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Sliding Mode Control of Vehicle Magnetorheological Semi-Active Air Suspension

Ruan

et al. 2021

Applied Sciences

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In order to reduce vehicle vibration during driving conditions, a fuzzy sliding mode control strategy (FSMC) for semi-active air suspension based on the magnetorheological (MR) damper is proposed. The MR damper used in the semi-active air suspension system was tested and analyzed. Based on the experimental data, the genetic algorithm was used to identify the parameters of the improved hyperbolic tangent model, which was derived for the MR damper. At the same time, an adaptive neuro fuzzy inference system (ANFIS) was used to build the reverse model of the MR damper. The model of a quarter vehicle semi-active air suspension system equipped with a MR damper was established. Aiming at the uncertainty of the air suspension system, fuzzy control was used to adjust the boundary layer of the sliding mode control, which can effectively suppress the influence of chattering on the control accuracy and ensure system stability. Taking random road excitation and impact road excitation as the input signal, the simulation analysis of passive air suspension, semi-active air suspension based on SMC and FSMC was carried out, respectively. The results show that the semi-active air suspension based on FSMC has better vibration attenuating performance and ride comfort.

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“…Fei and Wang (2020) designed a fractional-order current harmonic compensation controller by combining the fractional-order sliding mode theory and recurrent neural network, which improved the performance of the active power filter. For the purpose of modeling the magneto rheological damper based on semiactive vehicle suspensions more precisely and making sure the finite time convergence of the system, Nguyen et al (2020) proposed a fractional-order derivative based sliding mode controller and the validity of this controller is verified by numerical simulation. In order to enhance the output power quality of permanent magnet synchronous generator, Xiong et al (2020) proposed a fractional-order sliding mode control (FOSMC) method, which decided the controller coefficient boundaries and had stronger robustness, superior tracking precision and faster time response.…”

Section: Introductionmentioning

confidence: 99%

Design of Head Pursuit Guidance Law Based on Fractional-Order Sliding Mode Theory

Zhu

2021

J. Aerosp. Technol. Manag.

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This paper addresses problems on the interception of hypersonic vehicles in near-space. The main contribution is to study a head pursuit guidance law based on fractional-order sliding mode theory and analyze the stability of the guidance law provided. Firstly, the fractional-order differential operator, which has characteristics such as fast convergence and memory, is introduced into the design of sliding mode surface, based on which a head pursuit guidance can be designed to improve the performance of the guidance system. The stability of this guidance law is proved by Lyapunov stability theory. Based on this, a head pursuit guidance law considering autopilot dynamic characteristic is designed and the stability is also analyzed. Finally, numerical simulations are presented and the results verify that the guidance laws designed in this paper can avoid overload saturation at the initial moment of the terminal guidance stage and improve the convergence speed.

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Fractional-order sliding-mode controller for semi-active vehicle MRD suspensions

Cited by 28 publications

References 52 publications

Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system

Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system

Fuzzy Sliding Mode Control of Vehicle Magnetorheological Semi-Active Air Suspension

Design of Head Pursuit Guidance Law Based on Fractional-Order Sliding Mode Theory

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Fractional-order sliding-mode controller for semi-active vehicle MRD suspensions

Cited by 28 publications

References 52 publications

Research on nonlinear model and fuzzy fractional order PIλDμ control of air suspension system

Research on nonlinear model and fuzzy fractional order PIλDμ control of air suspension system

Fuzzy Sliding Mode Control of Vehicle Magnetorheological Semi-Active Air Suspension

Design of Head Pursuit Guidance Law Based on Fractional-Order Sliding Mode Theory

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Product

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Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system

Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system