Vehicle Handling and Stability Enhancement With Active Steering Control Systems

2004 ◽  
Author(s):  
Shih-Ken Chen ◽  
William C. Lin ◽  
Yuen-Kwok Steve Chin ◽  
Xiaodi Kang
Keyword(s):  
Rear Wheel ◽  
Front Wheel ◽  
Pole Placement ◽  
Optimization Approach ◽  
Steering Control ◽  
Response Characteristics ◽  
Active Steering ◽  
Road Surfaces ◽  
Response Optimization ◽  
Stability Enhancement

This paper presents an analysis and comparison of a vehicle with active front steering and rear-wheel steering. Based on linear analysis of base vehicle characteristics under varying speed and road surfaces, desirable vehicle response characteristics are presented and a set of performance matrices for active steering systems is formulated. Using pole-placement approach, controllability issues under active front wheel steering and rear- wheel steering controls are discussed. A frequency response optimization approach is then used to design the closed-loop controllers.

Research on Intelligent Information Technology with Intelligent Control of Full Aactive Steering Vehicle

2013 ◽  
Vol 473 ◽  
pp. 166-170
Author(s):  
Ling Yang ◽  
Zhi Wei Guan ◽  
Feng Du
Keyword(s):  
Information Technology ◽  
Rear Wheel ◽  
Steering Control ◽  
Response Characteristics ◽  
State Response ◽  
Active Steering ◽  
Intelligent Information ◽  
Vehicle Dynamic Model ◽  
Transient And Steady State ◽  
The Ideal

A new steering control strategy for active four-steering vehicle is studied based on the steering-by-wire and intelligent information technology in this paper. An ideal model-tracked of vehicle steering is established and an optimal active steering controller is designed on the basis of the 2 degree-of-freedom vehicle dynamic model. The simulation result shows that this optimal controller on front-rear wheel steering angle not only improve the transient and steady-state response characteristics of vehicle, but also follow the ideal steering model accurately. Therefore, the maneuverability and stability of vehicle are enhanced consequently.

Simulation of active steering control for the prevention of tractor dynamic rollover on random road surfaces

2019 ◽  
Vol 185 ◽  
pp. 135-149 ◽  
Author(s):  
Jiahao Qin ◽  
Zhehui Zhu ◽  
Hongyi Ji ◽  
Zhongxiang Zhu ◽  
Zhen Li ◽  
...  
Keyword(s):  
Steering Control ◽  
Active Steering ◽  
Road Surfaces ◽  
Active Steering Control

Steering control of six-wheeled vehicles using linear quadratic regulator techniques

2007 ◽  
Vol 221 (10) ◽  
pp. 1231-1240 ◽  
Author(s):  
B-C Chen ◽  
C-C Yu ◽  
W-F Hsu
Keyword(s):  
Linear Quadratic Regulator ◽  
Rear Wheel ◽  
Front Wheel ◽  
Open Loop ◽  
Slip Angle ◽  
Steering Control ◽  
Linear Quadratic ◽  
Integral Control ◽  
Side Slip Angle ◽  
Wheeled Vehicles

The middle- and rear-wheel steering angles of a six-wheeled vehicle need to be coordinated with the front-wheel steering angle to obtain the maximum manoeuvrability. A steering control strategy using the linear quadratic regulator technique with integral control is proposed in this paper such that both zero side-slip angle and target yaw rate following can be achieved simultaneously. An estimator to be used with the control law is also designed to provide the estimate of side-slip angle. AutoSim is used to establish a complex vehicle model with tyre dynamics in MATLAB/Simulink. Both open-loop and closed-loop manoeuvres are performed to evaluate the control performance of the proposed strategy.

Analysis of Steering Control Strategy on Tractor's Hydraulic Steering By-Wire System

2014 ◽  
Vol 487 ◽  
pp. 630-634 ◽  
Author(s):  
Zhi Xiong Lu ◽  
Jiang Xue Chang ◽  
Xue Feng Bai ◽  
Yang Lu ◽  
Jun Gan Wu
Keyword(s):  
Control Algorithm ◽  
Fast Response ◽  
Steering System ◽  
Front Wheel ◽  
Bench Test ◽  
Steering Control ◽  
Loop Control ◽  
Response Characteristics ◽  
Hydraulic Steering ◽  
Wire System

The structure and working principle of the hydraulic steering by-wire system were described, and the optimal control algorithm of the system was obtained by the comparative analysis. Fuzzy control was chosen as the steering systems control algorithm, and it can realize closed-loop control of the front wheel corner. Matlab/Simulink was used for the simulation of the entire system. The simulation got the fuel tank displacements response curve, and verified the accuracy of the system design, which can provide a reference to the design of tractors steering system. Bench test was proposed to verify the accuracy of the system. The bench test results showed that the hydraulic steering by-wire controller can realize systems steering function well, and the system improved the control accuracy and fast response characteristics.

scholarly journals Optimal Fractional PID Controller for Buck Converter Using Cohort Intelligent Algorithm

2021 ◽  
Vol 4 (3) ◽  
pp. 50
Author(s):  
Preeti Warrier ◽  
Pritesh Shah
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Power Converters ◽  
Buck Converter ◽  
Optimization Techniques ◽  
Superior Performance ◽  
Computational Time ◽  
Optimization Approach ◽  
Response Characteristics ◽  
Fractional Order Controller

The control of power converters is difficult due to their non-linear nature and, hence, the quest for smart and efficient controllers is continuous and ongoing. Fractional-order controllers have demonstrated superior performance in power electronic systems in recent years. However, it is a challenge to attain optimal parameters of the fractional-order controller for such types of systems. This article describes the optimal design of a fractional order PID (FOPID) controller for a buck converter using the cohort intelligence (CI) optimization approach. The CI is an artificial intelligence-based socio-inspired meta-heuristic algorithm, which has been inspired by the behavior of a group of candidates called a cohort. The FOPID controller parameters are designed for the minimization of various performance indices, with more emphasis on the integral squared error (ISE) performance index. The FOPID controller shows faster transient and dynamic response characteristics in comparison to the conventional PID controller. Comparison of the proposed method with different optimization techniques like the GA, PSO, ABC, and SA shows good results in lesser computational time. Hence the CI method can be effectively used for the optimal tuning of FOPID controllers, as it gives comparable results to other optimization algorithms at a much faster rate. Such controllers can be optimized for multiple objectives and used in the control of various power converters giving rise to more efficient systems catering to the Industry 4.0 standards.

Differential steering-based electric vehicle lateral dynamics control with rollover consideration

2019 ◽  
Vol 234 (3) ◽  
pp. 338-348
Author(s):  
Hui Jing ◽  
Rongrong Wang ◽  
Cong Li ◽  
Jinxiang Wang
Keyword(s):  
Electric Vehicles ◽  
Measurement Problem ◽  
Low Cost ◽  
Steering System ◽  
Front Wheel ◽  
Steering Control ◽  
Lateral Velocity ◽  
Lateral Dynamics ◽  
Vehicle Rollover ◽  
Differential Steering

This article investigates the differential steering-based schema to control the lateral and rollover motions of the in-wheel motor-driven electric vehicles. Generated from the different torque of the front two wheels, the differential steering control schema will be activated to function the driver’s request when the regular steering system is in failure, thus avoiding dangerous consequences for in-wheel motor electric vehicles. On the contrary, when the vehicle is approaching rollover, the torque difference between the front two wheels will be decreased rapidly, resulting in failure of differential steering. Then, the vehicle rollover characteristic is also considered in the control system to enhance the efficiency of the differential steering. In addition, to handle the low cost measurement problem of the reference of front wheel steering angle and the lateral velocity, an [Formula: see text] observer-based control schema is presented to regulate the vehicle stability and handling performance, simultaneously. Finally, the simulation is performed based on the CarSim–Simulink platform, and the results validate the effectiveness of the proposed control schema.

Feedback control framework for car-like robots using the unicycle controllers

Robotica ◽  
2011 ◽  
Vol 30 (4) ◽  
pp. 517-535 ◽  
Author(s):  
Maciej Michałek ◽  
Krzysztof Kozłowski
Keyword(s):  
Stability Analysis ◽  
Feedback Control ◽  
Closed Loop ◽  
Path Following ◽  
Rear Wheel ◽  
Front Wheel ◽  
Steering Angle ◽  
Formal Stability ◽  
Control Framework ◽  
Error Dynamics

SUMMARYThe paper introduces a novel general feedback control framework, which allows applying the motion controllers originally dedicated for the unicycle model to the motion task realization for the car-like kinematics. The concept is formulated for two practically meaningful motorizations: with a front-wheel driven and with a rear-wheel driven. All the three possible steering angle domains for car-like robots—limited and unlimited ones—are treated. Description of the method is complemented by the formal stability analysis of the closed-loop error dynamics. The effectiveness of the method and its limitations have been illustrated by numerous simulations conducted for the three main control tasks, namely, for trajectory tracking, path following, and set-point regulation.

scholarly journals Research on vehicle active steering control based on linear matrix inequality and hardware in the loop test scheme design and implement for active steering

2019 ◽  
Vol 11 (11) ◽  
pp. 168781401989210 ◽  
Author(s):  
Guangfei Xu ◽  
Peisong Diao ◽  
Xiangkun He ◽  
Jian Wu ◽  
Guosong Wang ◽  
...  
Keyword(s):  
Linear Matrix Inequality ◽  
Model Uncertainty ◽  
Control Method ◽  
Steering System ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Steering Control ◽  
Sensor Noise ◽  
Active Steering ◽  
Active Steering Control

In the research process of automotive active steering control, due to the model uncertainty, road surface interference, sensor noise, and other influences, the control accuracy of the active steering system will be reduced, and the driver’s road sense will become worse. The traditional robust controller can solve the model uncertainty, pavement disturbance and sensor noise in the design process, but cannot consider the performance enough. Therefore, this article proposes an active steering control method based on linear matrix inequality. In this method, the model uncertainty, road interference, sensor noise, yaw velocity, and slip side angle tracking errors are all considered as constraint targets, respectively, so that the performance and robust stability of the active front steering system can be guaranteed. Finally, simulation and hardware in the loop experiment are implemented to verify the effect of active front steering system under the linear matrix inequality controller. The results show that the proposed control method can achieve better robust performance and robust stability.

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