Cloud Model Approach for Lateral Control of Intelligent Vehicle Systems

Studies on intelligent vehicles, among which the controlling method of intelligent vehicles is a key technique, have drawn the attention of industry and the academe. This study focuses on designing an intelligent lateral control algorithm for vehicles at various speeds, formulating a strategy, introducing the Gauss cloud model and the cloud reasoning algorithm, and proposing a cloud control algorithm for calculating intelligent vehicle lateral offsets. A real vehicle test is applied to explain the implementation of the algorithm. Empirical results show that if the Gauss cloud model and the cloud reasoning algorithm are applied to calculate the lateral control offset and the vehicles drive at different speeds within a direction control area of ±7°, a stable control effect is achieved.

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Intelligent Car Direction Control Based on Fuzzy PID

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.466-467.1320 ◽

2012 ◽

Vol 466-467 ◽

pp. 1320-1324 ◽

Cited By ~ 2

Author(s):

Guo Liang ◽

Hong Li Gao ◽

Xiao Cheng Zhang

Keyword(s):

Pid Control ◽

Control Algorithm ◽

Response Speed ◽

Control Model ◽

Intelligent Vehicle ◽

Fuzzy Pid ◽

Fuzzy Pid Control ◽

Pid Algorithm ◽

Direction Control ◽

Control Response

Direction control is the decisive factors in intelligent car race. This paper used OV7620-CMOS as sensor, with steering gear as direction ac-tuators. Put forward intelligent car direction control model based on fuzzy PID algorithm. Experimental results show that fuzzy PID control algorithm is to improve the operation of the intelligent vehicle direction control response speed and the accuracy is very effective.

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Research on Lateral Control System for Intelligent Vehicle Based on Magnetic Markers Guidance

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.543-547.1340 ◽

2014 ◽

Vol 543-547 ◽

pp. 1340-1343

Author(s):

Fei Shen ◽

Feng Luo

Keyword(s):

Control System ◽

Intelligent Vehicles ◽

Intelligent Vehicle ◽

Vehicle Speed ◽

Lateral Control ◽

Good Reliability ◽

Magnetic Markers ◽

High Control ◽

Control Accuracy ◽

Real Vehicle

This paper presents the development of lateral control system for intelligent vehicle based on magnetic markers guidance. A lateral controller based on fuzzy logic is designed for intelligent vehicle that is non-linear controlled object. Simulation results show that the proposed control algorithm can ensure tracking reference path of intelligent vehicles accurately. The function of the system is finally verified by real vehicle experiment and the results show that the control system has high control accuracy, real-time performance and good reliability at an acceptable vehicle speed.

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Active control of the scattered radiation with a reflecting surface

Noise Control Engineering Journal ◽

10.3397/1/376717 ◽

2019 ◽

Vol 67 (3) ◽

pp. 190-196

Author(s):

Ning Han

Keyword(s):

Control System ◽

Active Control ◽

Scattered Radiation ◽

Sound Pressure ◽

Sound Field ◽

Control Area ◽

Mirror Image ◽

Three Dimension ◽

Control Effect ◽

Reflecting Surface

Based on a prediction method of the scattered sound pressure, an active control system was proposed in previous work for the three-dimension scattered radiation, where all the relevant simulations and experiments were implemented in three-dimensional free sound field. However, for practical applications, such as the anti-eavesdropping system or the stealth system for submarines, the sound field conditions are usually complex, and the most common case is the one with reflecting surface. It is questionable whether the previous control system is still effective in non-free sound field, or what improvements should be operated to ensure the control effect. In this article, based on the mirror image principle, two methods of calculating the control source strengths are proposed for the scattered radiation control, and numerical simulations with one-channel and multi-channel system are implemented to detect the corresponding control effect. It is seen that the local active control for the scattered radiation is still effective, and the reduction of the sound pressure level as well as the control area is extended with the increasement of the error sensors and control sources.

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Dynamic monitoring feedback iteration control for damping-adjustable semi-active suspension systems

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189719 ◽

2021 ◽

pp. 1-9

Author(s):

Chongchong Li ◽

Jiangyong Xiong ◽

Tingshan Liu ◽

Ziang Zhang

Keyword(s):

Root Mean Square ◽

Working Conditions ◽

Control Algorithm ◽

Active Suspension ◽

Dynamic Monitoring ◽

Iteration Algorithm ◽

Mean Square ◽

Control Effect ◽

Analytic Hierarchy ◽

Vehicle Simulation

In order to further improve vehicle ride performance, a dynamic monitoring feedback iteration control algorithm is proposed by combining the features of a variable-damping semi-active suspension system and applying them to the system. A seven-degree-of-freedom finished vehicle simulation model is built based on MATLAB/Simulink. The root-mean-square values of the acceleration of the sprung mass, the dynamic travel of the suspension and the dynamic tire load are taken as evaluation indicators of vehicle ride performance. An analytic hierarchy process (AHP) is used to determine the weighting coefficients of the evaluation indicators, and a genetic algorithm is utilized to determine the optimal damping of the suspension under various typical working conditions. Suspension damping is controlled with a dynamic monitoring feedback iteration algorithm. The correction coefficients of the control algorithm are determined according to the deviation between the obtained damping and the optimized damping so that the control parameters will agree with the optimal result under typical working conditions, and the control effect under other working conditions is verified. The simulation results indicate that the proposed dynamic monitoring feedback iteration control algorithm can effectively reduce the root-mean-square value of the acceleration of the sprung mass by 10.56% and the root-mean-square value of the acceleration of the dynamic travel of the suspension by 11.98% under mixed working conditions, thus improving vehicle ride performance. The study in this paper provides a new attempt for damping control of semi-active suspension and lays a theoretical foundation for its application in engineering.

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The Research of Air Precooling System Based on Generalize Predictive Control Strategy

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.433-435.1091 ◽

2013 ◽

Vol 433-435 ◽

pp. 1091-1098

Author(s):

Wei Bo Yu ◽

Cui Yuan Feng ◽

Ting Ting Yang ◽

Hong Jun Li

Keyword(s):

Predictive Control ◽

Control Strategy ◽

Control Algorithm ◽

Exchange Process ◽

Generalized Predictive Control ◽

Matlab Simulation ◽

Control Effect ◽

Heat Exchange Process ◽

Complex Control System ◽

And Control

The air precooling system heat exchange process is a complex control system with features such as: nonlinear, lag and random interference. So choose Generalized Predictive Control Algorithm that has low model dependence, good robustness and control effect, as well as easy to implement. But due to the large amount of calculation of traditional generalized predictive control and can't juggle quickness and overshoot problem, an improved generalized predictive control algorithm is proposed, then carry out the MATLAB simulation, the experimental results show that the algorithm can not only greatly reduce the amount of computation, but also can restrain the overshoot and its rapidity.

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Design and Lyapunov Stability Analysis of a Fuzzy Logic Controller for Autonomous Road Following

Mathematical Problems in Engineering ◽

10.1155/2010/578406 ◽

2010 ◽

Vol 2010 ◽

pp. 1-20 ◽

Cited By ~ 2

Author(s):

Yi Fu ◽

Howard Li ◽

Mary Kaye

Keyword(s):

Fuzzy Logic ◽

Stability Analysis ◽

Fuzzy Logic Controller ◽

Fuzzy Controller ◽

Intelligent Vehicles ◽

Intelligent Vehicle ◽

Rule Base ◽

Control Laws ◽

Robotic Vehicle ◽

Road Following

Autonomous road following is one of the major goals in intelligent vehicle applications. The development of an autonomous road following embedded system for intelligent vehicles is the focus of this paper. A fuzzy logic controller (FLC) is designed for vision-based autonomous road following. The stability analysis of this control system is addressed. Lyapunov's direct method is utilized to formulate a class of control laws that guarantee the convergence of the steering error. Certain requirements for the control laws are presented for designers to choose a suitable rule base for the fuzzy controller in order to make the system stable. Stability of the proposed fuzzy controller is guaranteed theoretically and also demonstrated by simulation studies and experiments. Simulations using the model of the four degree of freedom nonholonomic robotic vehicle are conducted to investigate the performance of the fuzzy controller. The proposed fuzzy controller can achieve the desired steering angle and make the robotic vehicle follow the road successfully. Experiments show that the developed intelligent vehicle is able to follow a mocked road autonomously.

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