Automatic parking control system based on self-adaptive neural network constraint control

An automatic parking and neural network technology, applied in adaptive control, general control system, control/regulation system, etc., can solve the problems of wheel steering angle not being able to track the set value, fast parking troubles, etc.

Inactive Publication Date: 2017-08-18
JIANGNAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing automatic parking system, due to the saturation problem of the wheel steering angle, is similar to the problem of not being able to track the set value, which causes unnecessary troubles for quick parking

Method used

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  • Automatic parking control system based on self-adaptive neural network constraint control
  • Automatic parking control system based on self-adaptive neural network constraint control
  • Automatic parking control system based on self-adaptive neural network constraint control

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Embodiment 1

[0066] An automatic parking control system based on adaptive neural network constraint control of the present invention takes the vehicle steering angle as the object, and uses an anti-saturation compensator to correct the angle control method of the PID controller based on the RBF neural network. The design block diagram is as follows figure 1 shown.

[0067] The automatic parking control system mainly includes: path planning module, PID controller based on RBF neural network, dynamic constraint module, anti-saturation compensator, vehicle dynamics model and observer based on RBF neural network. The RBF observer outputs the Jacobian information to the PID controller and the anti-saturation compensator; the PID controller calculates and obtains the actual value of the wheel steering angle, and the input of the anti-saturation compensator is the constrained wheel steering angle and the unconstrained The difference of the steering angle of the wheels is processed by the anti-sat...

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Abstract

The invention discloses an automatic parking control system based on self-adaptive neural network constraint control, and belongs to the intelligent vehicle technology field. The automatic parking control system comprises path planning based on an ultrasonic sensor, a PID controller based on an RBF neural network, dynamic constraint restriction, a complete vehicle dynamical model, and an observer and an anti-saturation compensator based on the RBF neural network. By adopting the above mentioned structure and considering an input constraint restriction condition, the whole system has a complete control idea. According to an actual condition, and after being verfied by simulation examples, the automatic parking control system has advantages of good tracking performance, robustness, and adaptability.

Description

technical field [0001] The invention relates to an automatic parking control system based on adaptive neural network constraint control, which belongs to the technical field of intelligent vehicles. Background technique [0002] Parking in dense urban areas is a painful experience for many drivers. With limited parking space in big cities, maneuvering a car into tight spaces has become a must-have skill. Rarely does a car stop without a lot of trouble, and a bad stop can lead to traffic jams, driver nervous fatigue, or the bumper being bent. Automatic parking technology can effectively solve the above problems, enabling cars to park safely and quickly in designated areas. [0003] Automatic parking technology is gradually maturing. The automatic parking system of the prior art has the problem of being unable to track the set value due to the saturation problem of the wheel steering angle, which causes unnecessary troubles for fast parking. Contents of the invention [...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 许德智宋晓麒邓竞颜文旭
Owner JIANGNAN UNIV
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