Artificial Intelligence Control Algorithm for the Steering Motion of Wheeled Soccer Robot

2019 ◽  
Vol 33 (10) ◽  
pp. 1959034 ◽  
Author(s):  
Xiaowei Xiong
Keyword(s):  
Artificial Intelligence ◽  
Control Algorithm ◽  
Steering Wheel ◽  
Dynamic Feedback ◽  
Steering Control ◽  
Soccer Robot ◽  
Artificial Neurons ◽  
Intelligence Control ◽  
Intelligent Model ◽  
Soccer Robots

In this paper, the artificial intelligence control algorithm for steering robot of steering wheel is studied. The steering movement of wheeled soccer robot is controlled by artificial intelligence control algorithm, and the steering movement is modeled and simulated. Firstly, the characteristics of artificial neurons are simulated and a similar control model is constructed to complete the simulation of football. The artificial intelligence control algorithm has a dynamic feedback item compared with the traditional intelligent model, which has a better effect on the steering control of the wheeled soccer robot. In this paper, artificial intelligence control algorithm is used to optimize the parameters of artificial intelligence control algorithm, and the output of control signal of each steering part of wheeled soccer robot is simulated in the experiment, and the control of the steering action of wheeled soccer robot by artificial intelligence control algorithm is verified by experiments. Then the artificial intelligence control algorithm forms the connection structure. This method provides a good reference for steering control of wheeled soccer robots.

scholarly journals Research on Control of Intelligent Vehicle Human-Simulated Steering System Based on HSIC

2019 ◽  
Vol 9 (5) ◽  
pp. 905 ◽  
Author(s):  
Haobin Jiang ◽  
Huan Tian ◽  
Yiding Hua ◽  
Bin Tang
Keyword(s):  
Intelligent Control ◽  
Control Algorithm ◽  
Rapid Prototype ◽  
Steering System ◽  
Steering Wheel ◽  
Intelligent Vehicle ◽  
System Control ◽  
Steering Control ◽  
Nonlinear Fitting ◽  
Resistance Torque

The experienced drivers with good driving skills are used as objects of learning, and road steering test data of skilled drivers are collected in this article. First, a nonlinear fitting was made to the driving trajectory of skilled driver in order to achieve human-simulated control. The segmental polynomial expression was solved for two typical steering conditions of normal right-steering and U-turn, and the hp adaptive pseudo-spectral method was used to solve the connection problem of the vehicle segmental driving trajectory. Second, a new Electric Power Steering (EPS) system was proposed, and the intelligent vehicle human-simulated steering system control model based on human simulated intelligent control (HSIC) was established in Simulink/Carsim joint simulation environment to simulate and analyze. Finally, in order to further verify the effectiveness of the proposed algorithm in this article, an intelligent vehicle steering system test bench with a steering resistance torque simulation device was built, and the dSPACE rapid prototype controller was used to realize human-simulated intelligent control law. The results show that the human-simulated steering control algorithm is superior to the traditional proportion integration differentiation (PID) control in the tracking effect of the steering characteristic parameters and passenger comfort. The steering wheel angle and torque can better track the angle and torque variation curve of real vehicle steering experiment of the skilled driver, and the effectiveness of the intelligent vehicle human-simulated steering control algorithm based on HSIC proposed in this article is verified.

Intermittent Predictive Steering Control as an Automobile Driver Model

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
Rene Roy ◽  
Philippe Micheau ◽  
Paul Bourassa
Keyword(s):  
Control Algorithm ◽  
Driver Model ◽  
Steering Wheel ◽  
Intermittent Control ◽  
Steering Control ◽  
Period Range ◽  
The Road ◽  
Wide Range ◽  
Safety Systems ◽  
General Predictive Control

The originality of this paper is the evaluation of intermittent control as a viable candidate to represent an automobile driver in a path tracking scenario. The control algorithm is based on general predictive control where the road curvature is considered known for a horizon in front of the automobile. The computed steering wheel command is used in an intermittent fashion, the intermittence period being one of the system parameter to study. Simulations are carried out and parameters of the driver, the automobile, and the road are varied. An intermittence period range giving satisfactory performances is observed. A comparison is made with actual car/driver behavior measurements for a lane change maneuver. It is concluded that, according to this driver model, there is a wide range of intermittence period that the automobile driver may be operating. Moreover, it is suggested to consider the intermittency of information as an important parameter for vehicle safety systems.

Driver Steering Control and a New Perspective on Car Handling Qualities

2005 ◽  
Vol 219 (10) ◽  
pp. 1041-1051 ◽  
Author(s):  
R S Sharp
Keyword(s):  
White Noise ◽  
Gaussian White Noise ◽  
Design Parameters ◽  
Steering Wheel ◽  
Steering Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Handling Qualities ◽  
Gaussian White Noise Process ◽  
Low Pass

The article is about steering control of cars by drivers, concentrating on following the lateral profile of the roadway, which is presumed visible ahead of the car. It builds on previously published work, in which it was shown how the driver's preview of the roadway can be combined with the linear dynamics of a simple car to yield a problem of discrete-time optimal-linear-control-theory form. In that work, it was shown how an optimal ‘driver’ of a linear car can convert the path preview sample values, modelled as deriving from a Gaussian white-noise process, into steering wheel displacement commands to cause the car to follow the previewed path with an attractive compromise between precision and ease. Recognizing that real roadway excitation is not so rich in high frequencies as white-noise, a low-pass filter is added to the system. The white-noise sample values are filtered before being seen by the driver. Numerical results are used to show that the optimal preview control is unaltered by the inclusion of the low-pass filter, whereas the feedback control is affected diminishingly as the preview increases. Then, using the established theoretical basis, new results are generated to show time-invariant optimal preview controls for cars and drivers with different layouts and priorities. Tight and loose controls, representing different balances between tracking accuracy and control effort, are calculated and illustrated through simulation. A new performance criterion with handling qualities implications is set up, involving the minimization of the preview distance required. The sensitivities of this distance to variations in the car design parameters are calculated. The influence of additional rear wheel steering is studied from the viewpoint of the preview distance required and the form of the optimal preview gain sequence. Path-following simulations are used to illustrate relatively high-authority and relatively low-authority control strategies, showing manoeuvring well in advance of a turn under appropriate circumstances. The results yield new insights into driver steering control behaviour and vehicle design optimization. The article concludes with a discussion of research in progress aimed at a further improved understanding of how drivers control their vehicles.

Effectiveness of the running system of a wheeled vehicle

2020 ◽  
pp. 16-22
Author(s):  
D.A. Dubovik
Keyword(s):  
Steering Wheel ◽  
Steering Control ◽  
Control Effectiveness ◽  
Power Drive ◽  
Running System ◽  
Wheeled Vehicle ◽  
Curvilinear Motion ◽  
Wheeled Vehicles ◽  
System Power ◽  
Effectiveness Coefficient

A method for quantitative assessment of the effectiveness of the running system of wheeled vehicles for the general case of curvilinear motion is proposed. An expression is obtained for calculating the coefficient of efficiency of the running system of a wheeled vehicle, taking into account the parameters of the power and steering wheel drives. The results of evaluating the effectiveness of the running system of an off-road vehicle with a wheel arrangement of 8Ѕ8 and two front steerable axles are presented. Keywords: wheeled vehicle, running system, power drive, drive wheels, steering control, effectiveness, coefficient of efficiency. [email protected]

Co-Simulation of Power Steering Control and Vehicle Dynamic Responses

2001 ◽  
Author(s):  
Gene Y. Liao
Keyword(s):  
Dynamic Model ◽  
General Purpose ◽  
Dynamic Responses ◽  
Steering Wheel ◽  
Vehicle Dynamic ◽  
Steering Control ◽  
Integrated Simulation ◽  
Full Vehicle ◽  
Power Steering ◽  
Vehicle Dynamic Model

Abstract Many general-purpose and specialized simulation codes are becoming more flexible which allows analyses to be carried out simultaneously in a coupled manner called co-simulation. Using co-simulation technique, this paper develops an integrated simulation of an Electric Power Steering (EPS) control system with a full vehicle dynamic model. A full vehicle dynamic model interacting with EPS control algorithm is concurrently simulated on a single bump road condition. The effects of EPS on the vehicle dynamic behavior and handling responses resulting from steer and road input are analyzed and compared with proving ground experimental data. The comparisons show reasonable agreement on tie-rod load, rack displacement, steering wheel torque and tire center acceleration. This developed co-simulation capability may be useful for EPS performance evaluation and calibration as well as for vehicle handling performance integration.

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