scholarly journals Active Suspension Control of Eight Degrees of Freedom Vehicle Model

2004 ◽  
Vol 9 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Rahmi Guclu
Keyword(s):  
Degrees Of Freedom ◽  
Active Suspension ◽  
Vehicle Model ◽  
Suspension Control

The Implementation of Skyhook Control for Semi-Active Suspension Based on Vi-CarRealTime

2015 ◽  
Vol 713-715 ◽  
pp. 748-751 ◽  
Author(s):  
Bo Wei Bi ◽  
Fang Xiao
Keyword(s):  
Control Strategy ◽  
Ride Comfort ◽  
Active Suspension ◽  
Vehicle Model ◽  
Control Range ◽  
Control Signals ◽  
Suspension Control ◽  
Automobile Suspension ◽  
Simulation Results ◽  
Damper Control

The research of semi active suspension control strategy once was a hot point in the field of automobile suspension [2, 3], but it is difficult to achieve for most of them. I choose VI-CarRealTime to build vehicle model based on ADAMS vehicle model. Kalman Filter designed based on 1/2 vehicle model supply control signals for controller. Considering characteristics of CDC damper, Skyhook control strategy is applied for simulation, the simulation results show that, Skyhook Control can improve vehicle ride comfort in CDC damper control range.

Design of an Active Suspension Control for a Four DOF Model Using Genetic Algorithm

2005 ◽  
Author(s):  
S. Gosselin-Brisson ◽  
M. Bouazara ◽  
M. J. Richard
Keyword(s):  
Genetic Algorithm ◽  
Degrees Of Freedom ◽  
Real Life ◽  
Active Suspension ◽  
Performance Criterion ◽  
Control Methods ◽  
Frequency Sensitivity ◽  
Suspension Control ◽  
Passive Suspension System ◽  
Real Vehicle

This paper presents the design of an active suspension controller for an automotive vehicle. A four degrees of freedom linear model is used to represent a vehicle with different front and rear characteristics. Filtered road and acceleration inputs are applied to the model to simulate real life use. The performance criterion are filtered to include frequency sensitivity and weighted based on a standard passive suspension system. Independent front and rear controllers are optimised with the genetic algorithm. The controller includes linear gains and frequency dependency to take advantage of these two different control methods. The number of sensors and the order of the filters are limited to facilitate implementation on a real vehicle.

scholarly journals The Design of LQG Controller for Active Suspension Based on Analytic Hierarchy Process

2010 ◽  
Vol 2010 ◽  
pp. 1-19 ◽  
Author(s):  
Lingjiang Chai ◽  
Tao Sun
Keyword(s):  
Analytic Hierarchy Process ◽  
Degrees Of Freedom ◽  
Active Suspension ◽  
Ride Quality ◽  
Linear Quadratic ◽  
Analytic Hierarchy ◽  
Performance Indexes ◽  
Suspension Control ◽  
Hierarchy Process ◽  
Selection Of

A full vehicle model with seven degrees of freedom based on active suspension control is established, and linear quadratic gaussian (LQG) is designed by applying optimal control theory. Especially, the methodology of Analytic Hierarchy Process (AHP) is used to make the selection of weighted coefficients of performance indexes, which can reduce ineffective job in contrast with experience method. From the simulation results, it is shown that ride quality of the vehicle with active suspension has been effectively improved in comparison with the vehicle of passive suspension by the methodology of AHP applying to the selection of the weights.

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.

Optimal Preview Semiactive Suspension

1996 ◽  
Vol 118 (1) ◽  
pp. 99-105 ◽  
Author(s):  
L. Jezequel ◽  
V. Roberti
Keyword(s):  
Degrees Of Freedom ◽  
Active Suspension ◽  
Control Law ◽  
Semiactive Control ◽  
Active System ◽  
Two Degrees Of Freedom ◽  
Suspension Control ◽  
Computer Controlled ◽  
Track Irregularities ◽  
Semiactive Suspension

This paper examines an optimal preview semiactive suspension of a quarter-coach model moving along randomly profiled track. This optimal computer-controlled suspension is designed only to dissipate energy, and is able to use knowledge of track irregularities over a distance L in front of the train. Thus the deformation of the track can be taken into account when calculating the semi-active suspension control law. First, the expression of the optimal preview semiactive control law is established. Then, using a two-degrees-of-freedom quarter-coach model, preview information is shown to improve the behavior of an optimal non-preview semi-active system, which can come close to the performance of an active system.

Simulation of Hydraulic Semi-Active Suspension System Based on the Adaptive Fuzzy Control

2011 ◽  
Vol 48-49 ◽  
pp. 1065-1068
Author(s):  
Zhi Xuan Jia ◽  
Hui Gang Zhang ◽  
Jie Li
Keyword(s):  
Fuzzy Control ◽  
Degrees Of Freedom ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Active Suspension ◽  
Vertical Vibration ◽  
Suspension System ◽  
Suspension Control ◽  
Suspension Model ◽  
Suspension Structure

According to vehicle suspension structure, a 2-DOF (degrees of freedom) semi-active hydraulic suspension model for 1/4 vehicle is built. Fuzzy control as a result of simple modeling, with high precision control and non-linear adaptive advantages of the vehicle active suspension control strategy, has been a wider application. In this paper, the body’s speed and acceleration were selected for the fuzzy controller inputs, damper output, to realize the semi-active suspension control. Taking some type of vehicle as the simulation object, this paper uses Matlab/Simulink for computer simulation in the same road conditions. And the performance parameters of improving vehicle vertical vibration are compared to the passive suspension. The results show that the semi-active suspension system strategy by fuzzy control can obviously improve the comfortable and safe ride.

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.

Sign in / Sign up

Export Citation Format

Share Document