scholarly journals A Case Study on Computer-Based Analysis of the Stochastic Stability of Mechanical Structures Driven by White and Colored Noise: Utilizing Artificial Intelligence Techniques to Design an Effective Active Suspension System

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Aydin Azizi
Keyword(s):  
Artificial Intelligence ◽  
Gaussian White Noise ◽  
Active Suspension ◽  
Suspension System ◽  
Probabilistic Logic ◽  
Pavement Condition ◽  
The Road ◽  
Road Profile ◽  
Effective Performance ◽  
White And Colored Noise

The goal of this research is to design an Artificial Intelligence controller for the active suspension system of vehicles. The Ring Probabilistic Logic Neural Network (RPLNN) architecture has been adopted to design the proposed controller, and the pavement condition has been modelled utilizing Gaussian white noise. The results show that the proposed RPLNN controller has an effective performance to reduce the unwanted stochastic effect of the road profile.

scholarly journals Computer-Based Analysis of the Stochastic Stability of Mechanical Structures Driven by White and Colored Noise

2018 ◽  
Vol 10 (10) ◽  
pp. 3419 ◽  
Author(s):  
Aydin Azizi
Keyword(s):  
White Noise ◽  
Pid Controller ◽  
Colored Noise ◽  
Gaussian White Noise ◽  
Active Suspension ◽  
Suspension System ◽  
Pavement Condition ◽  
White And Colored Noise ◽  
Computer Based ◽  
Environment Sustainability

The goal of this paper is to design an effective Proportional Integral Derivative (PID) controller, which will control the active suspension system of a car, in order to eliminate the imposed vibration to the car from pavement. In this research, Gaussian white noise has been adopted to model the pavement condition, and MATLAB/Simulink software has been used to design a PID controller, as well as to model the effect of the white noise on active suspension system. The results show that the designed controller is effective in eliminating the effect of road conditions. This has a significant effect on reducing the fuel consumption and contributes to environment sustainability.

scholarly journals The algorithm of adaptive control for active suspension systems using pole assign and cascade design method

2020 ◽  
Vol 9 (4) ◽  
pp. 271
Author(s):  
Chi Nguyen Van
Keyword(s):  
Control Method ◽  
Reference Model ◽  
Active Suspension ◽  
Suspension System ◽  
Control Force ◽  
Control Loop ◽  
The Road ◽  
Suspension Systems ◽  
Road Profile ◽  
Control Scheme

This paper presents the active suspension system (ASS) control method using the adaptive cascade control scheme. The control scheme is implemented by two control loops, the inner control loop and outer control loop are designed respectively. The inner control loop uses the pole assignment method in order to move the poles of the original system to desired poles respect to the required performance of the suspension system. To design the controller in the inner loop, the model without the noise caused by the road profile and velocity of the car is used. The outer control loop then designed with an adaptive mechanism calculates the active control force to compensate for the vibrations caused by the road profile and velocity of the car. The control force is determined by the error between states of the reference model and states of suspension systems, the reference model is the model of closed-loop with inner control loop without the noise. The simulation results implemented by using the practice date of the road profile show that the capability of oscillation decrease for ASS is quite efficient

scholarly journals Experimental Researches on the Dynamic Behavior of the Magnetorheological Damper

2020 ◽  
Author(s):  
Alexandru Dobre
Keyword(s):  
Dynamic Behavior ◽  
Shock Absorber ◽  
Active Suspension ◽  
Suspension System ◽  
Magnetorheological Damper ◽  
Passenger Cars ◽  
Damping Force ◽  
The Road ◽  
Shock Absorbers ◽  
Road Profile

In the context of improving the comfort and dynamics of the vehicle, the suspension system has been continuously developed and improved, especially using magnetorheological (MR) shock absorbers. The development of this technology which is relatively new has not been easy. Thus, the first widespread commercial use of MR fluid in a semi-active suspension system was implemented in passenger cars. The magnetorheological shock absorber can combine the comfort with the dynamic driving, because it allows the damping characteristic to be adapted to the road profile. The main objective of the paper is to analyze the dynamic behavior of the magnetorheological shock absorber in the semi-active suspension. In this sense, the author carried out a set of experimental measurements with a damping test bench, specially built and equipped with modern equipment. The results obtained from the experimental determinations show a significantly improved comfort when using a magnetorheological shock absorber, compared to a classic one, by the fact that the magnetorheological shock absorber allows to modify the damping coefficient according to the road conditions, thus maintaining the permanent contact between the tire and the road due to increased damping force.

scholarly journals Effect of Road Profile on Suspension System of Heavy Truck

2019 ◽  
Vol 12 (2) ◽  
pp. 71-75
Author(s):  
Salem F. Salman
Keyword(s):  
Steering System ◽  
Suspension System ◽  
The Road ◽  
Road Profile ◽  
Road Roughness ◽  
Road Type ◽  
Heavy Truck ◽  
Main Factors ◽  
On The Road ◽  
The Stability

All vehicles are affected by the type of the road they are moving on it.  Therefore the stability depends mainly on the amount of vibrations and steering system, which in turn depend on two main factors: the first is on the road type, which specifies the amount of vibrations arising from the movement of the wheels above it, and the second on is the type of the used suspension system, and how the parts connect with each other. As well as the damping factors, the tires type, and the used sprungs. In the current study, we will examine the effect of the road roughness on the performance coefficients (speed, displacement, and acceleration) of the joint points by using a BOGE device.

Influence of the road profile accuracy on disturbance compensation in active suspension systems

2021 ◽  
Vol 69 (6) ◽  
pp. 485-498
Author(s):  
Felix Anhalt ◽  
Boris Lohmann
Keyword(s):  
Ride Comfort ◽  
Feedforward Control ◽  
Active Suspension ◽  
Disturbance Compensation ◽  
Critical Factors ◽  
The Road ◽  
Suspension Systems ◽  
Active Suspension Systems ◽  
Road Profile ◽  
Profile Accuracy

Abstract By applying disturbance feedforward control in active suspension systems, knowledge of the road profile can be used to increase ride comfort and safety. As the assumed road profile will never match the real one perfectly, we examine the performance of different disturbance compensators under various deteriorations of the assumed road profile using both synthetic and measured profiles and two quarter vehicle models of different complexity. While a generally valid statement on the maximum tolerable deterioration cannot be made, we identify particularly critical factors and derive recommendations for practical use.

scholarly journals Online Reinforcement Learning-Based Control of an Active Suspension System Using the Actor Critic Approach

2020 ◽  
Vol 10 (22) ◽  
pp. 8060
Author(s):  
Ahmad Fares ◽  
Ahmad Bani Younes
Keyword(s):  
Reinforcement Learning ◽  
Least Squares Method ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Suspension System ◽  
Recursive Least Squares ◽  
Linear Quadratic ◽  
Reward Function ◽  
Road Profile ◽  
The One

In this paper, a controller learns to adaptively control an active suspension system using reinforcement learning without prior knowledge of the environment. The Temporal Difference (TD) advantage actor critic algorithm is used with the appropriate reward function. The actor produces the actions, and the critic criticizes the actions taken based on the new state of the system. During the training process, a simple and uniform road profile is used while maintaining constant system parameters. The controller is tested using two road profiles: the first one is similar to the one used during the training, while the other one is bumpy with an extended range. The performance of the controller is compared with the Linear Quadratic Regulator (LQR) and optimum Proportional-Integral-Derivative (PID), and the adaptiveness is tested by estimating some of the system’s parameters using the Recursive Least Squares method (RLS). The results show that the controller outperforms the LQR in terms of the lower overshoot and the PID in terms of reducing the acceleration.

scholarly journals Road Profile Estimation Using a 3D Sensor and Intelligent Vehicle

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3676 ◽  
Author(s):  
Tao Ni ◽  
Wenhang Li ◽  
Dingxuan Zhao ◽  
Zhifei Kong
Keyword(s):  
Real Time ◽  
Autonomous Vehicles ◽  
Active Suspension ◽  
Suspension System ◽  
Global Navigation Satellite Systems ◽  
Cloud Data ◽  
Uneven Terrain ◽  
Road Profile ◽  
Data Points ◽  
Profile Estimation

Autonomous vehicles can achieve accurate localization and real-time road information perception using sensors such as global navigation satellite systems (GNSSs), light detection and ranging (LiDAR), and inertial measurement units (IMUs). With road information, vehicles can navigate autonomously to a given position without traffic accidents. However, most of the research on autonomous vehicles has paid little attention to road profile information, which is a significant reference for vehicles driving on uneven terrain. Most vehicles experience violent vibrations when driving on uneven terrain, which reduce the accuracy and stability of data obtained by LiDAR and IMUs. Vehicles with an active suspension system, on the other hand, can maintain stability on uneven roads, which further guarantees sensor accuracy. In this paper, we propose a novel method for road profile estimation using LiDAR and vehicles with an active suspension system. In the former, 3D laser scanners, IMU, and GPS were used to obtain accurate pose information and real-time cloud data points, which were added to an elevation map. In the latter, the elevation map was further processed by a Kalman filter algorithm to fuse multiple cloud data points at the same cell of the map. The model predictive control (MPC) method is proposed to control the active suspension system to maintain vehicle stability, thus further reducing drifts of LiDAR and IMU data. The proposed method was carried out in outdoor environments, and the experiment results demonstrated its accuracy and effectiveness.

scholarly journals Design of LQG Controller for Active Suspension without Considering Road Input Signals

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Hui Pang ◽  
Ying Chen ◽  
JiaNan Chen ◽  
Xue Liu
Keyword(s):  
Angular Acceleration ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Body ◽  
Vehicle Suspension ◽  
Linear Quadratic ◽  
The Road ◽  
Input Signals ◽  
Vehicle Suspension System ◽  
Weight Coefficients

As the road conditions are completely unknown in the design of a suspension controller, an improved linear quadratic and Gaussian distributed (LQG) controller is proposed for active suspension system without considering road input signals. The main purpose is to optimize the vehicle body acceleration, pitching angular acceleration, displacement of suspension system, and tire dynamic deflection comprehensively. Meanwhile, it will extend the applicability of the LQG controller. Firstly, the half-vehicle and road input mathematical models of an active suspension system are established, with the weight coefficients of each evaluating indicator optimized by using genetic algorithm (GA). Then, a simulation model is built in Matlab/Simulink environment. Finally, a comparison of simulation is conducted to illustrate that the proposed LQG controller can obtain the better comprehensive performance of vehicle suspension system and improve riding comfort and handling safety compared to the conventional one.

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