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

Singh, Devdutt; Aggarwal, Manjeet

doi:10.1007/s40435-015-0175-0

Cited by 22 publications

(17 citation statements)

References 34 publications

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“…The primary contribution of this paper lies in the application of a fuzzy combination of fuzzy and fuzzy self-tuning PID controllers. A quarter car model with MR damper with three degrees of freedom (3DOF) is formulated for each uncontrolled, fuzzy controlled, HFPID controlled as proposed by (Singh & Aggarwal, 2017) and HFFPID controlled systems. The model is examined for two kinds of excitations, namely those generated by a bump road and random road profiles, by using Simulations are carried out by Matlab/ Simulink software.…”

Section: Introductionmentioning

confidence: 99%

Ride Comfort Improvement of a Semi-active Vehicle Suspension Based on Hybrid Fuzzy and Fuzzy-PID Controller

Bashir¹,

Rui²,

Zhang³

2019

SIC

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The development of vehicles providing maximum drive comfort and handling stability is one of the design targets for car manufacturers. This paper proposes a hybrid fuzzy and fuzzy-PID (HFFPID) controller for a semi-active quarter-car with three degrees of freedom utilizing a magneto-rheological (MR) shock absorber. The control objective is to amend the ride quality of the vehicle. The proposed controller comprises a fuzzy-self-tuned proportional-integral-derivative (FSTPID) controller, a fuzzy-logic controller (FLC) and a fuzzy selector (FS). Based on the error between the output and its set point, the fuzzy selector selects which controller should play the greatest effect on the control system. The effectiveness of the proposed control strategy is analysed through simulations involving excitations for a bump road and a random road profile in time domain. The results show that the HFFPID controller has the best performance in reducing the car body acceleration, suspension working space and seat acceleration response compared with the uncontrolled as well as FLC-and HFPID controlled-cases. Hence, the best ride quality response is provided by the HFFPID controller as compared to all the other suspension systems considered in this paper.

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Section: Introductionmentioning

confidence: 99%

Ride Comfort Improvement of a Semi-active Vehicle Suspension Based on Hybrid Fuzzy and Fuzzy-PID Controller

Bashir¹,

Rui²,

Zhang³

2019

SIC

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“…The block diagram of the FLST-PID is shown in Figure 2. [14,18,27,28], the trial and error method and the experience of the authors and are shown in Figure 3. The state variables, sprung mass velocity and accelerations used in this work are measured by using velocity sensors or accelerometers.…”

Section: Controller Design For the Semi-active Seat Suspensionmentioning

confidence: 99%

“…Singh and Aggarwal [14] analysed the passenger seat vibration of the semi-active quarter car model with a hybrid Fuzzy-PID control. They reported that the proposed Fuzzy-PID approach offered a better performance in terms of passenger seat acceleration and displacement.…”

Section: Introductionmentioning

confidence: 99%

Performance Investigation of Integrated Model of Quarter Car Semi-Active Seat Suspension with Human Model

et al. 2020

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In this paper, an integrated model of a semi-active seat suspension with a human model over a quarter is presented. The proposed eight-degrees of freedom (8-DOF) integrated model consists of 2-DOF for the quarter car model, 2-DOF for the semi-active seat suspension and 4-DOF for the human model. A magneto-rheological (MR) damper is implemented for the seat suspension. The fuzzy logic-based self-tuning (FLST) proportional–integral–derivative (PID) controller allows to regulate the controlled force on the basis of sprung mass velocity error and its derivative as input. The controlled force is tracked by the Heaviside step function which determines the supply voltage for the MR damper. The performance of the proposed integrated model is analysed, in-terms of human head accelerations, for several road profiles and at different speeds. The performance of the semi-active seat suspension is compared with the traditional passive seat suspension to validate the effectiveness of the proposed integrated model with a semi-active seat suspension. The simulation results show that the semi-active seat suspension improves the ride comfort significantly by reducing the head acceleration effectively compared to the passive seat suspension.

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“…The dynamic differential equation of the vertical motion of four unsprung mass is listed as shown in equation (3).…”

Section: Dynamic Differential Equationmentioning

confidence: 99%

“…Ren et al presented an adaptive hybrid control algorithm combined with the ground-hook and skyhook control strategies based on quarter car model of semiactive suspension and designed an unscented Kalman filter to estimate the suspension states [2]. Singh and Aggarwal designed a hybrid Fuzzy-PID controller to evaluate the passenger ride comfort based on a semiactive quarter car model having MR shock absorber [3]. Du et al presented an approach in designing a robust controller for half-car model active suspensions considering changes in vehicle inertial properties, such as the suspension deflection limitation and the controller saturation problem [4].…”

Section: Introductionmentioning

confidence: 99%

Modelling and Analysis of Automobile Vibration System Based on Fuzzy Theory under Different Road Excitation Information

Chen

Zhou

2018

Complexity

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A fuzzy increment controller is designed aimed at the vibration system of automobile active suspension with seven degrees of freedom (DOF). For decreasing vibration, an active control force is acquired by created Proportion-Integration-Differentiation (PID) controller. The controller's parameters are adjusted by a fuzzy increment controller with self-modifying parameters functions, which adopts the deviation and its rate of change of the body's vertical vibration velocity and the desired value in the position of the front and rear suspension as the input variables based on 49 fuzzy control rules. Adopting Simulink, the fuzzy increment controller is validated under different road excitation, such as the white noise input with four-wheel correlation in time-domain, the sinusoidal input, and the pulse input of C-grade road surface. The simulation results show that the proposed controller can reduce obviously the vehicle vibration compared to other independent control types in performance indexes, such as, the root mean square value of the body's vertical vibration acceleration, pitching, and rolling angular acceleration.

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

Cited by 22 publications

References 34 publications

Ride Comfort Improvement of a Semi-active Vehicle Suspension Based on Hybrid Fuzzy and Fuzzy-PID Controller

Ride Comfort Improvement of a Semi-active Vehicle Suspension Based on Hybrid Fuzzy and Fuzzy-PID Controller

Performance Investigation of Integrated Model of Quarter Car Semi-Active Seat Suspension with Human Model

Modelling and Analysis of Automobile Vibration System Based on Fuzzy Theory under Different Road Excitation Information

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