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Genetic algorithm optimization-based vehicle rear-end collision fuzzy control method

A genetic algorithm and fuzzy control technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve problems such as the difficulty of precise mathematical models

Active Publication Date: 2015-05-20
XIDIAN UNIV
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Problems solved by technology

[0008] The purpose of the present invention is to provide a vehicle rear-end collision fuzzy control method based on genetic algorithm optimization, aiming to solve the problem that existing auxiliary control or automatic control methods are difficult to obtain the precise mathematical model of the vehicle, and the control method is restricted in the active control of the vehicle. developmental issues

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  • Genetic algorithm optimization-based vehicle rear-end collision fuzzy control method
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  • Genetic algorithm optimization-based vehicle rear-end collision fuzzy control method

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[0068] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0069] The application principle of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0070] Such as figure 1 As shown, the fuzzy control method of vehicle rear-end collision collision based on genetic algorithm optimization in the embodiment of the present invention comprises the following steps:

[0071] The present invention designs a double-input and single-output fuzzy controller. Select the relative distance error ds and the relative speed error dv of the front and rear vehicles as the input variables of the fuzzy controller, and the actua...

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Abstract

The invention discloses a genetic algorithm optimization-based vehicle rear-end collision fuzzy control method. The genetic algorithm optimization-based vehicle rear-end collision fuzzy control method is performed by a dual-input and single-output fuzzy controller. Relative distance error ds and relative speed error dv are selected to serve as input variables of the fuzzy controller, and accelerated speed Fad control amount which is actually output serves as an output variable. A genetic algorithm optimization fuzzy control rule is used, so that the performance of a vehicle control system is improved, the response speed is high, the avoidance of occurrence of a rear-end collision accident is facilitated, the energy consumption of a vehicle is reduced, and the control effect on collision avoidance is achieved.

Description

technical field [0001] The invention belongs to the technical field of vehicle control, in particular to a fuzzy control method for vehicle rear-end collision based on genetic algorithm optimization. Background technique [0002] The risk of a rear-end collision between the front and rear vehicles is high, and auxiliary control or automatic control should be adopted to avoid the risk. In the past, some scholars have proposed a variety of classic control methods, such as: PID control, sliding mode control and linear quadratic optimal control. However, although the above-mentioned classical control method can provide a certain precise control effect, it must be established on the basis of an accurate mathematical model. In practice, it is usually difficult to obtain an accurate mathematical model of the vehicle, thus restricting the development of the above-mentioned control methods in the aspect of vehicle active control. [0003] In addition, some scholars have proposed a ...

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Application Information

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IPC IPC(8): G05B13/04G08G1/16
Inventor 陈晨李美莲项红玉裴庆祺魏康文吕宁
Owner XIDIAN UNIV
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