Control of Handling Stability in Four-Wheel Steering Vehicles Based on Individual Channel Design

2011 ◽  
Vol 480-481 ◽  
pp. 1074-1078 ◽  
Author(s):  
Bin Yang ◽  
Mao Song Wan ◽  
Qing Hong Sun
Keyword(s):  
Linear Model ◽  
Control Structure ◽  
Steering System ◽  
Steering Control ◽  
Channel Design ◽  
Lateral Dynamics ◽  
Yaw Rate ◽  
System A ◽  
Design Paradigm ◽  
The Individual

This paper presents a new steering control structure for vehicles equipped with four-wheel steering system. A linear model of the lateral dynamics is used in this paper. This control structure is based on a simplified linear model of the lateral dynamics of such vehicles and aims to decouple the control of sideslip from the control of yaw rate. The control design is based on a linear multivariable plant and the front and rear steering angles, According to the Individual Channel Design paradigm. The proposed control structure has been applied to design sideslip and yaw rate controllers using a more accurate model of the lateral dynamics of four-wheel steering vehicles. Simulations are used to illustrate the performance and robustness of the designed controllers.

A Study on Integrated Control for Four-Wheel Steering System to Enhance Vehicle Lateral Stability

2012 ◽  
Vol 466-467 ◽  
pp. 1285-1289
Author(s):  
Bin Yang ◽  
Mao Song Wan ◽  
Qing Hong Sun
Keyword(s):  
Integrated Control ◽  
Steering System ◽  
Dynamics Model ◽  
Lateral Dynamics ◽  
Yaw Rate ◽  
Design Paradigm ◽  
Nonlinear Dynamics Model ◽  
The Individual ◽  
Good Vehicle ◽  
Integrated Control System

This paper presents the design of integrated control for four-wheel steering (4WS) vehicle. A vehicle nonlinear dynamics model is built based on a lateral dynamics simplified linear model. A more accurate sideslip and yaw rate controller is used for lateral dynamics model of 4WS vehicle. Then a vehicle model based on the individual channel and partial decoupling design paradigm is identified from the vehicle dynamics. The sideslip and yaw rate controller is based on a linear multivariable combined with lateral dynamics model and the front and rear steering angles. The results of a stability analysis and simulations are presented to show that the 4WS integrated control system can markedly enhance good vehicle lateral maneuverability.

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.

scholarly journals Experimental Study of Electric Vehicle Yaw Rate Tracking Control Based on Differential Steering

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Cong Li ◽  
Yun-Feng Xie ◽  
Gang Wang ◽  
Su-Qi Liu ◽  
Bing Kuang ◽  
...  
Keyword(s):  
Experimental Study ◽  
Electric Vehicle ◽  
Tracking Control ◽  
Steering System ◽  
Test Results ◽  
Steering Control ◽  
Yaw Rate ◽  
Steer By Wire ◽  
Differential Steering ◽  
Steering Force

This paper investigates the experimental study of differential steering control of a four-wheel independently driven (FWID) electric vehicle (EV) based on the steer-by-wire (SBW) system. As each wheel of FWID vehicle can be independently driven, differential steering is realized by applying different driven torques to the front-two wheels. Firstly, the principle of the differential steering is analyzed based on the SBW system. When the differential steering is activated, the driver’s steering request is sent to the vehicle’s ECU. Then, the ECU gives different control signals to the front-left and front-right wheels, generating an external steering force on the steering components. The external steering force pushes the steering components to turn corresponding to the driver’s request. Secondly, to test the feasibility of differential steering, a FWID EV is assembled and the vehicle is equipped with four independently driven in-wheel motors. The corresponding control system is designed. Finally, the field test of the vehicle based on the proposed differential steering control strategy is performed. In the experiment, the fixed yaw rate tracking and varied yaw rate tracking maneuvers are employed. In the fixed yaw rate tracking, the vehicle can track the desired yaw rate well with differential steering. In addition, the vehicle can track the varied yaw rate with proposed differential steering. The test results confirm the feasibility and effectiveness of the differential steering. By using the differential steering, a backup steering is established without additional components; thus, the costs can be reduced and the reliability of the vehicle steering system can be enhanced, significantly.

Comparison of Analytical and Empirical Models to Capture Variations in Off-Road Vehicle Dynamics

2005 ◽  
Author(s):  
Paul J. Pearson ◽  
David M. Bevly
Keyword(s):  
Empirical Data ◽  
Vehicle Dynamics ◽  
Experimental Validation ◽  
Inertial Sensors ◽  
Analytical Models ◽  
Control Algorithms ◽  
Model Parameters ◽  
Steering Control ◽  
Steering Angle ◽  
Yaw Rate

This paper develops two analytical models that describe the yaw dynamics of a farm tractor and can be used to design or improve steering control algorithms for the tractor. These models are verified against empirical data. The particular dynamics described are the motions from steering angle to yaw rate. A John Deere 8420 tractor, outfitted with inertial sensors and controlled through a PC-104 form factor computer, was used for experimental validation. Conditions including different implements at varying depths, as would normally be found on a farm, were tested. This paper presents the development of the analytical models, validates them against empirical data, and gives trends on how the model parameters change for different configurations.

scholarly journals Decentralized Optimization for a Novel Control Structure of HVAC System

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Shiqiang Wang ◽  
Jianchun Xing ◽  
Ziyan Jiang ◽  
Juelong Li
Keyword(s):  
Control System ◽  
Decentralized Control ◽  
Control Structure ◽  
Optimization Method ◽  
Labor Cost ◽  
Smart Device ◽  
Hvac System ◽  
Decentralized Optimization ◽  
System A ◽  
Novel Method

A decentralized control structure is introduced into the heating, ventilation, and air conditioning (HVAC) system to solve the high maintenance and labor cost problem in actual engineering. Based on this new control system, a decentralized optimization method is presented for sensor fault repair and optimal group control of HVAC equipment. Convergence property of the novel method is theoretically analyzed considering both convex and nonconvex systems with constraints. In this decentralized control system, traditional device is fitted with a control chip such that it becomes a smart device. The smart device can communicate and operate collaboratively with the other devices to accomplish some designated tasks. The effectiveness of the presented method is verified by simulations and hardware tests.

scholarly journals Modeling of Tractor Fuel Consumption

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2300
Author(s):  
Bronisław Andrzej Kolator
Keyword(s):  
Fuel Consumption ◽  
Soil Conditions ◽  
Simulation Studies ◽  
Working Capacity ◽  
Operational Parameters ◽  
System A ◽  
The Individual ◽  
Adjustment System ◽  
Unit Performance ◽  
Efficiency Indicators

In this paper, the energy diagnostic of tractor performance consists in evaluating the energy (fuel consumption per hectare—dm3 ha−1) for a given agricultural operation and in combining it with working capacity, also called productivity (area productivity—ha h−1). One of the methods of solving this problem is the identification of the functioning process of the machine unit. A model of the process of the machine unit performance was developed, considering the operation of the rear linkage system of the implement with the force control adjustment system. In order to analyze the system, a mathematical model of the system function was built: tractor-implement-soil, defining the physical connections and interdependencies between the individual subsystems of the system. Based on this model, a simulation model was developed and implemented in the Matlab/Simulink environment. The Simulink package was used to test the performance of the machine set. The efficiency indicators according to the adopted criteria were calculated in the evaluation block. To evaluate the process, the technical and operational parameters of the tractor, the type and parameters of the tool, and soil properties were taken into account. The results of simulation studies obtained on a validated model are consistent with experimental data from appropriate soil conditions.

Global adaptive neural backstepping control of a flexible hypersonic vehicle with disturbance estimation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
He-Wei Zhao ◽  
Li-bin Yang
Keyword(s):  
Rbf Neural Network ◽  
Tracking Error ◽  
Hypersonic Vehicle ◽  
Nonlinear Dynamic Model ◽  
Content Type ◽  
Lateral Dynamics ◽  
Disturbance Estimation ◽  
System A ◽  
Complexity Problem ◽  
Velocity Tracking

Purpose This paper aims to discuss the precise altitude and velocity tracking control of a hypersonic vehicle, a global adaptive neural backstepping controller was studied based on a disturbance observer (DOB). Design/methodology/approach The DOB combined with a radial basis function (RBF) neural network (NN) was used to estimate the disturbance terms that are generated by the flexible modes of the hypersonic vehicle system. A global adaptive neural method was introduced to approximate the unknown system dynamics, with robust control terms pulling the system transient states back into the neural approximation domain externally. Findings The globally uniformly ultimately bounded for all signals of a closed-loop system can be guaranteed by the proposed control algorithm. Additionally, the command filtered backstepping methods can avoid the explosion of the complexity problem caused by the backstepping design process. In addition, the effectiveness of the proposed controller can be verified by the simulation used in this study. Research limitations/implications Normally lateral dynamics issue should be discussed in the process of control system designed, the lateral dynamics are not included in the nonlinear dynamic model of hypersonic vehicle used in this paper, merely the longitudinal flight dynamics are discussed in this paper. Originality/value The flexible states in rigid modes are considered as the disturbance of the system, which is estimated by structuring DOB with NN approximations. The compensating tracking error and prediction error are used in the update law of RBF NN weight. The differential explosions complexity derived from the backstepping procedure is dealt with by using command filters.

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