Unmanned mine truck robust path tracking control method

By constructing a time-varying uncertain dynamic model and a preview kinematic model, combining knowledge-driven and data-driven methods, and designing multiple angle control rates, the problems of path tracking accuracy and stability of unmanned mining trucks in the complex environment of open-pit mines were solved, and efficient path tracking control was achieved.

CN120742895APending Publication Date: 2025-10-03HUNAN UNIV
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Patent Information

Application Number
CN202510916587.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-03
Publication Date
2025-10-03

AI Technical Summary

Technical Problem

Unmanned mining trucks have poor path tracking accuracy and stability in the complex driving environment of open-pit mines. Affected by multi-source uncertainty, the existing control algorithms have weak adaptability and robustness.

Method used

A time-varying uncertain dynamic model and a preview kinematic model are constructed. Combining knowledge-driven and data-driven methods, the nominal steering angle control rate, error feedback steering angle control rate and robust steering angle control rate are designed. The steering action is executed through the front-wheel steering mechanism to achieve path tracking control.

Benefits of technology

It significantly improves the path tracking accuracy and vehicle stability of unmanned mining trucks under multi-source time-varying uncertainties, reduces computational complexity, and enhances adaptability and robustness to complex mining environments.

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Abstract

The invention discloses an unmanned mine truck robust path tracking control method. The method comprises the following steps: acquiring an expected path, vehicle type parameters, a global position and real-time state information; starting a robust path tracking control function, constructing a time-varying uncertain dynamic model and a preview kinematics model, and integrating a control target into a servo equality constraint; collecting vehicle state and constraint following error information, establishing a knowledge-driven off-line data set, and obtaining accurately estimated system uncertainty through off-line training; according to the estimated system uncertainty, on-line compensation is carried out on an estimation error based on an attenuation type adaptive rate, and an accurately represented system uncertainty boundary is output; a robust steering angle control rate and an error feedback control rate are designed, a nominal steering angle control rate is combined to jointly form final front wheel steering angle control input, the final front wheel steering angle control input is sent to a front wheel steering mechanism to execute a steering action, and the path tracking precision and stability of the unmanned mine truck under the multi-source uncertainty of speed fluctuation, uneven road surface, lateral wind and the like are improved.
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