Hybrid Fuzzy Skyhook Surface Control Using Multi-Objective Microgenetic Algorithm for Semi-Active Vehicle Suspension System Ride Comfort Stability Analysis

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Yi Chen ◽  
Zhong-Lai Wang ◽  
Jing Qiu ◽  
Hong-Zhong Huang
Keyword(s):  
Stability Analysis ◽  
Real Time ◽  
Ride Comfort ◽  
Polynomial Function ◽  
Sliding Mode ◽  
Initial Conditions ◽  
Active Suspension ◽  
Suspension System ◽  
Multi Objective ◽  
Microgenetic Algorithm

A polynomial function supervising fuzzy sliding mode control (PSFαSMC), which embedded with skyhook surface method, is proposed for the ride comfort of a vehicle semi-active suspension. The multi-objective microgenetic algorithm (MOμGA) has been utilized to determine the PSFαSMC controller’s parameter alignment in a training process with three ride comfort objectives for the vehicle semi-active suspension, which is called the “offline” step. Then, the optimized parameters are applied to the real-time control process by the polynomial function supervising controller, which is named “online” step. A two-degree-of-freedom dynamic model of the vehicle semi-active suspension systems with the stability analysis is given for passenger’s ride comfort enhancement studies, and a simulation with the given initial conditions has been devised in MATLAB. The numerical results have shown that this hybrid control method is able to provide real-time enhanced level of reliable ride comfort performance for the semi-active suspension system.

Performance analysis of MR damper based semi-active suspension system using optimally tuned controllers

2021 ◽  
pp. 095440702110044
Author(s):  
Gurubasavaraju Tharehalli mata ◽  
Vijay Mokenapalli ◽  
Hemanth Krishna
Keyword(s):  
Pid Controller ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Parametric Method ◽  
Mr Damper ◽  
Active Suspension ◽  
Suspension System ◽  
Sliding Mode Controller ◽  
Road Excitation

This study assesses the dynamic performance of the semi-active quarter car vehicle under random road conditions through a new approach. The monotube MR damper is modelled using non-parametric method based on the dynamic characteristics obtained from the experiments. This model is used as the variable damper in a semi-active suspension. In order to control the vibration caused under random road excitation, an optimal sliding mode controller (SMC) is utilised. Particle swarm optimisation (PSO) is coupled to identify the parameters of the SMC. Three optimal criteria are used for determining the best sliding mode controller parameters which are later used in estimating the ride comfort and road handling of a semi-active suspension system. A comparison between the SMC, Skyhook, Ground hook and PID controller suggests that the optimal parameters with SMC have better controllability than the PID controller. SMC has also provided better controllability than the PID controller at higher road roughness.

Online Adaptive Neuro-Fuzzy Based Full Car Suspension Control Strategy

2015 ◽  
pp. 992-1039
Author(s):  
Laiq Khan ◽  
Shahid Qamar
Keyword(s):  
Degrees Of Freedom ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Active Suspension ◽  
Suspension System ◽  
Car Model ◽  
Car Suspension ◽  
Neuro Fuzzy ◽  
Suspension Control ◽  
Soft Computing Technique

Suspension system of a vehicle is used to minimize the effect of different road disturbances for ride comfort and improvement of vehicle control. A passive suspension system responds only to the deflection of the strut. The main objective of this work is to design an efficient active suspension control for a full car model with 8-Degrees Of Freedom (DOF) using adaptive soft-computing technique. So, in this study, an Adaptive Neuro-Fuzzy based Sliding Mode Control (ANFSMC) strategy is used for full car active suspension control to improve the ride comfort and vehicle stability. The detailed mathematical model of ANFSMC has been developed and successfully applied to a full car model. The robustness of the presented ANFSMC has been proved on the basis of different performance indices. The analysis of MATLAB/SMULINK based simulation results reveals that the proposed ANFSMC has better ride comfort and vehicle handling as compared to Adaptive PID (APID), Adaptive Mamdani Fuzzy Logic (AMFL), passive, and semi-active suspension systems. The performance of the active suspension has been optimized in terms of displacement of seat, heave, pitch, and roll.

scholarly journals Hybrid Modelling and Sliding Mode Control of Semi-Active Suspension Systems for Both Ride Comfort and Road-Holding

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1286
Author(s):  
Ayman Aljarbouh ◽  
Muhammad Fayaz
Keyword(s):  
Hybrid Model ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Suspension ◽  
Suspension Systems ◽  
Active Suspension Systems ◽  
System Components ◽  
And Control

Rigorous model-based design and control for intelligent vehicle suspension systems play an important role in providing better driving characteristics such as passenger comfort and road-holding capability. This paper investigates a new technique for modelling, simulation and control of semi-active suspension systems supporting both ride comfort and road-holding driving characteristics and implements the technique in accordance with the functional mock-up interface standard FMI 2.0. Firstly, we provide a control-oriented hybrid model of a quarter car semi-active suspension system. The resulting quarter car hybrid model is used to develop a sliding mode controller that supports both ride comfort and road-holding capability. Both the hybrid model and controller are then implemented conforming to the functional mock-up interface standard FMI 2.0. The aim of the FMI-based implementation is to serve as a portable test bench for control applications of vehicle suspension systems. It fully supports the exchange of the suspension system components as functional mock-up units (FMUs) among different modelling and simulation platforms, which allows re-usability and facilitates the interoperation and integration of the suspension system components with embedded software components. The concepts are validated with simulation results throughout the paper.

scholarly journals Design and Development of an Active Suspension System Using Pneumatic-Muscle Actuator and Intelligent Control

2019 ◽  
Vol 9 (20) ◽  
pp. 4453 ◽  
Author(s):  
I-Hsum Li ◽  
Lian-Wang Lee
Keyword(s):  
Ride Comfort ◽  
Controller Design ◽  
Sliding Mode ◽  
Active Suspension ◽  
Suspension System ◽  
Vertical Force ◽  
Time Varying ◽  
Pneumatic Muscle ◽  
Pneumatic Muscle Actuator ◽  
Stability And Accuracy

A pneumatic muscle is a cheap, clean, and high-power active actuator. However, it is difficult to control due to its inherent nonlinearity and time-varying characteristics. This paper presents a pneumatic muscle active suspension system (PM-ASS) for vehicles and uses an experimental study to analyze its stability and accuracy in terms of reducing vibration. In the PM-ASS, the pneumatic muscle actuator is designed in parallel with two MacPherson struts to provide a vertical force between the chassis and the wheel. This geometric arrangement allows the PM-ASS to produce the maximum force to counter road vibration and make the MacPherson struts generate significant improvement. In terms of the controller design, this paper uses an adaptive Fourier neural network sliding-mode controller with H ∞ tracking performance for the PM-ASS, which confronts nonlinearities and time-varying characteristics. A state-predictor is used to predict the output error and to provide the predictions for the controller. Experiments with a rough concave-convex road and a two-bump excitation road use a quarter-car test rig to verify the practical feasibility of the PM-ASS, and the results show that the PM-ASS gives an improvement the ride comfort.

scholarly journals Active Control of Nonlinear Suspension System Using Modified Adaptive Supertwisting Controller

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Jagat J. Rath ◽  
Kalyana C. Veluvolu ◽  
Michael Defoort
Keyword(s):  
Active Control ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Active Suspension ◽  
Higher Order ◽  
Suspension System ◽  
Road Surface ◽  
Control Action ◽  
The Road ◽  
Bounded Uncertainties

The suspension system is faced with nonlinearities from the spring, damper, and external excitations from the road surface. The objective of any control action provided to the suspension is to improve ride comfort while ensuring road holding for the vehicle. In this work, a robust higher order sliding mode algorithm combining the merits of the modified supertwisting algorithm and the adaptive supertwisting algorithm has been proposed for the nonlinear active suspension system. The proposed controller is robust to linearly growing perturbations and bounded uncertainties. Simulations have been performed for different classes of road excitations and the results are presented.

scholarly journals Nonlinear Predictive Sliding Mode Control for Active Suspension System

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Dazhuang Wang ◽  
Dingxuan Zhao ◽  
Mingde Gong ◽  
Bin Yang
Keyword(s):  
Sliding Mode Control ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Approximation Error ◽  
Nonlinear Effects ◽  
Active Suspension ◽  
Adaptive Controller ◽  
Suspension System ◽  
Mode Control ◽  
Stability Performance

An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

Design and optimization of a semi-active suspension system for a two-wheeled vehicle using a full multibody model

2016 ◽  
Vol 231 (4) ◽  
pp. 630-646 ◽  
Author(s):  
A Khadr ◽  
A Houidi ◽  
L Romdhane
Keyword(s):  
Ride Comfort ◽  
Optimization Procedure ◽  
Active Suspension ◽  
Suspension System ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Passive Suspension ◽  
Multi Objective ◽  
Wheeled Vehicle ◽  
Passive Suspension System

This paper focuses on the design and the optimization of a semi-active suspension system used in a full dynamic model of a two-wheeled vehicle. The two-wheeled vehicle is considered as a multibody system. The equations of motion are obtained by applying an approach used widely in the robotic modeling field. Two basic strategies, called the continuous skyhook and the modified skyhook, are used to control the semi-active suspension system. Using the developed model, a multi-objective optimization procedure, based on Genetic Algorithms (NSGA-II), is proposed. The objective is to optimize the parameters of the two control laws of the semi-active suspension systems, in order to improve the ride comfort and the safety. To study the effectiveness of this approach, the results of the optimization are used in different simulations and the results are compared with those obtained from a simulation of a two-wheeled vehicle equipped with a passive suspension system. The results show that both control strategies of the semi-active suspension system give an improvement compared to the passive suspension system. Moreover, the multi-objective optimization results show that the simplified law “Modified Skyhook” ensures a higher ride safety, whereas the “Continuous Skyhook” is more effective in obtaining a higher level of ride comfort.

Online Adaptive Neuro-Fuzzy Based Full Car Suspension Control Strategy

2014 ◽  
pp. 617-666 ◽  
Author(s):  
Laiq Khan ◽  
Shahid Qamar
Keyword(s):  
Degrees Of Freedom ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Active Suspension ◽  
Suspension System ◽  
Car Model ◽  
Car Suspension ◽  
Neuro Fuzzy ◽  
Suspension Control ◽  
Soft Computing Technique

Suspension system of a vehicle is used to minimize the effect of different road disturbances for ride comfort and improvement of vehicle control. A passive suspension system responds only to the deflection of the strut. The main objective of this work is to design an efficient active suspension control for a full car model with 8-Degrees Of Freedom (DOF) using adaptive soft-computing technique. So, in this study, an Adaptive Neuro-Fuzzy based Sliding Mode Control (ANFSMC) strategy is used for full car active suspension control to improve the ride comfort and vehicle stability. The detailed mathematical model of ANFSMC has been developed and successfully applied to a full car model. The robustness of the presented ANFSMC has been proved on the basis of different performance indices. The analysis of MATLAB/SMULINK based simulation results reveals that the proposed ANFSMC has better ride comfort and vehicle handling as compared to Adaptive PID (APID), Adaptive Mamdani Fuzzy Logic (AMFL), passive, and semi-active suspension systems. The performance of the active suspension has been optimized in terms of displacement of seat, heave, pitch, and roll.

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