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

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.

Study on Control Technology of Active Suspension Based on ADAMS and MATLAB

2014 ◽  
Vol 602-605 ◽  
pp. 1372-1377 ◽  
Author(s):  
Yi Zhang ◽  
Li Li Sun
Keyword(s):  
Pid Control ◽  
Ride Comfort ◽  
Active Suspension ◽  
Vertical Vibration ◽  
Vehicle Suspension ◽  
Control Effect ◽  
Vibration Acceleration ◽  
Suspension Control ◽  
Suspension Model ◽  
Control Principle

In order to improve the control effect of vehicle suspension, the simplified Seven-DOF active suspension model was created in ADAMS/View by applying the dynamics theory, and classical PID control principle was utilized to design an active suspension controller for vehicle. The vehicle model was imported into the PID controller established in MATLAB as a module to create a vehicle active suspension control model. According to the simulation results, compared with passive suspension, the PID control of active suspension can control effectively the vertical vibration acceleration (VVA),roll and pitch acceleration (RAA&PAA) of body ,which improved vehicle ride comfort performance.

A Novel Fuzzy Controller to Improve Desired Suspension Performance

2007 ◽  
Author(s):  
Mohammad Biglarbegian ◽  
William Melek ◽  
Farid Golnaraghi
Keyword(s):  
Degrees Of Freedom ◽  
Ride Comfort ◽  
Fuzzy Controller ◽  
Active Suspension ◽  
Suspension System ◽  
Suspension Systems ◽  
System A ◽  
Active Suspension Systems ◽  
Vehicle Suspension System ◽  
Suspension Performance

Semi-active suspension systems allow for adjusting the vehicle shock damping and hence improved suspension performance can be achieved over passive methods. This paper presents the design of a novel fuzzy control structure to concurrently improve ride comfort and road handling of vehicles with semi-active suspension system. A full car model with seven degrees of freedom is adopted that includes the vertical, roll, and pitch motions as well as the vertical motions of each wheel. Four decentralized fuzzy controllers are developed and applied to each individual damper in the vehicle suspension system. Mamdani’s method is applied to infer the damping coefficient output from the fuzzy controller. To evaluate the performance of the proposed controller, numerical analyses were carried out on a real road bump. Moreover, results were compared with well-known and widely used controllers such as Skyhook. It is shown that the proposed fuzzy controller is capable of achieving enhanced ride comfort and road handling over other widely used control methods.

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.

The CO-Simulation Research of Vehicle Active Suspension Based on Fuzzy Control

2013 ◽  
Vol 668 ◽  
pp. 415-419
Author(s):  
Zhi Gang Huang ◽  
Jin Gang Ding ◽  
Ke Liu ◽  
Xiao Dong Bao
Keyword(s):  
Fuzzy Control ◽  
Dynamic Model ◽  
Vehicle Dynamics ◽  
Fuzzy Controller ◽  
Simulation Analysis ◽  
Active Suspension ◽  
Simulation Research ◽  
Matlab Simulink ◽  
The Road ◽  
Suspension Model

Based on the vehicle dynamics theory, the 2-DOF active suspension model was studied to establish its dynamic model and the road model. Besides, the fuzzy controller were designed with dynamic deflection of the suspension as the controlling object. The 2-DOF active suspension model was established in Adams/View and the stochastic uneven road model was established in Matlab/Simulink in combination of the fuzzy controller to joint CO-Simulation analysis . The results show that the active suspension can effectively suppress vehicle vibration, and improve the riding performance and security.

A Research on Simulation for Semi-Active Suspension Control Based on Immune Algorithm

2013 ◽  
Vol 694-697 ◽  
pp. 2035-2039
Author(s):  
Guang Xing Tan ◽  
Wen Guo Jian ◽  
Shan Li ◽  
Xin Peng Ye
Keyword(s):  
Fuzzy Logic Control ◽  
Degrees Of Freedom ◽  
Active Suspension ◽  
Immune Algorithm ◽  
Vertical Acceleration ◽  
Passive Suspension ◽  
Logic Control ◽  
Suspension Control ◽  
Control Capability ◽  
Suspension Model

Based on two-degrees-of-freedom (2-DOFs) quarter-car semi-active suspension model, a method for semi-active suspension control is proposed based on immune algorithm. According to this algorithm, an immune controller is designed to research and simulation for semi-active suspension control. Simulation results show that the proposed algorithm is effective，and compared with the passive suspension and fuzzy logic control (FLC) algorithm, its control capability is the best. Using immune controller, the RMS of body vertical acceleration, tire loads and suspension distortion are significantly reduced, so vehicle ride performance, handling stability are effectively improved.

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

2014 ◽  
Vol 556-562 ◽  
pp. 1472-1475 ◽  
Author(s):  
Bing Dong ◽  
Yan Tao Tian ◽  
Chang Jiu Zhou
Keyword(s):  
Dynamic Programming ◽  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management System ◽  
Control Method ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Energy Management System ◽  
Fuzzy Control Strategy

This thesis puts forward one optimal adaptive fuzzy control method based on the pure electric vehicle energy management system of the fuzzy control which has been founded already. By adding an optimizing researching model based on the conventional fuzzy control strategy, the thesis can pick up the valuable control rules based on the dynamic programming theory and also can adjust the parameter of the fuzzy controller automatically according to the system operating. These can make the sum of the energy loss reduce to the min. The experiment points out that this method makes the vehicle possess good economic performance in the same driving cycle.

Sign in / Sign up

Export Citation Format

Share Document