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A track following method based on a neural network and a PID algorithm

A neural network and algorithm technology, applied in attitude control and other directions, to achieve good robustness, fast real-time performance, and good adaptability

Active Publication Date: 2016-06-22
WUHAN KOTEI INFORMATICS
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Problems solved by technology

With the development of the industry, the complexity of the object continues to deepen, especially for the large lag, time-varying, nonlinear complex intelligent driving vehicle control system, the conventional PID control is powerless
Therefore, the application of conventional PID control is greatly restricted and challenged

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  • A track following method based on a neural network and a PID algorithm
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  • A track following method based on a neural network and a PID algorithm

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Embodiment Construction

[0013] like figure 1 As shown, the present invention provides a kind of trajectory following method based on neural network and PID algorithm, and it comprises the following steps:

[0014] S1. Obtain the expected driving trajectory parameter value, the driving trajectory parameter value including position coordinate value, heading angle, speed and angular velocity;

[0015] S2, obtaining the current vehicle's driving trajectory parameter value, and predicting the driving trajectory parameter value of the vehicle after the vehicle motion model;

[0016] S3, using the performance function to obtain an error value according to the expected driving trajectory parameter value obtained in step S1 and the predicted driving trajectory parameter value;

[0017] S4, input the error value obtained in step S3 into the PID controller to obtain the steering wheel angle, and control the steering of the vehicle according to the angle;

[0018] S5, repeat steps S2 and S3 to obtain the error...

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Abstract

The invention provides a track following method based on a neural network and a PID algorithm, and is mainly used for a tracking scheme of an intelligent driving automobile on a driving map. Normal PID control is combined with neural network control to give play to respective advantages thereof to form so-called intelligent PID control. The method can enable the intelligent driving automobile to follow an expected track; a control system designed through adoption of a neural network method has better real-time performance, stronger adaptability and higher robustness. Computer simulation experiments and real automobile experiments show that the control based on the neural network and the PID algorithm has better real-time performance, stronger adaptability and good control results compared with normal PID control.

Description

technical field [0001] The invention relates to unmanned driving technology, in particular to a trajectory following method based on a neural network and a PID algorithm. Background technique [0002] PID control is one of the earliest control strategies developed using classical control theory. Due to its simple algorithm, good robustness and high reliability, it is widely used in industrial processes and has achieved good control results. With the development of the industry, the complexity of the object continues to deepen, especially for the large lag, time-varying, nonlinear complex intelligent driving vehicle control system, the conventional PID control is powerless. Therefore, the application of conventional PID control is greatly restricted and challenged. [0003] The application of neural network in the control system improves the information system processing ability and adaptability of the whole system, and improves the intelligence level of the system. In addi...

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Application Information

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IPC IPC(8): G05D1/08
CPCG05D1/08
Inventor 王军德吴鑫崔鹏
Owner WUHAN KOTEI INFORMATICS
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