Adaptive control system and method for cutting transmission system of coal cutter under complex working condition

By using an adaptive torque compensation control system, combined with a second-order nonlinear active disturbance rejection torque module and an adaptive convolutional neural network fuzzy module, the dynamic load suppression problem of the coal mining machine cutting transmission system under complex working conditions is solved, the adaptive adjustment of system parameters is realized, and the safety and production efficiency of the coal mining machine are improved.

WO2026051158A1 Publication Date: 2026-03-12JIANGSU ZHONGJI MINE EQUIP +1
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Patent Information

Application Number
PCT/CN2024/125444
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-09-04
Filing Date
2024-10-17
Publication Date
2026-03-12

AI Technical Summary

Technical Problem

Existing technologies are insufficient to effectively suppress the dynamic load impact of the coal mining machine's cutting transmission system under complex working conditions and to achieve adaptive adjustment of system parameters, making it difficult for the coal mining machine to maintain its optimal working state under different cutting conditions.

Method used

An adaptive torque compensation control system is adopted, including a sample construction module, an adaptive torque compensation controller, a superposition module, and a cutting motor speed adjustment module. The controller output is adaptively adjusted by using a second-order nonlinear active disturbance rejection torque module, an adaptive convolutional neural network fuzzy module, and a BP neural network. Combined with multi-layer convolutional neural network and fuzzy control, adaptive compensation of the system is achieved.

Benefits of technology

It effectively suppresses dynamic load impacts under complex working conditions, improves the safety and production efficiency of the coal mining machine, realizes adaptive adjustment of system parameters, improves control accuracy and response speed, and reduces sensitivity to time-varying parameters.

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Abstract

Disclosed in the present invention are an adaptive control system and method for a cutting transmission system of a coal cutter under complex working conditions. An extended state observer in an adaptive torque compensation controller tracks state variables of a cutting transmission system, and estimates in real time disturbances of the system such as nonlinearity and time-varying parameters, so as to compensate a real-time action amount of a total disturbance into an actual control amount for feedforward compensation on disturbance terms; a BP network adaptively adjusts parameters of a second-order active disturbance rejection torque controller; an adaptive convolutional neural network fuzzy module realizes an adaptive adjustment for an output compensation of the active disturbance rejection torque compensation controller, so as to obtain an expert control rule that meets complex impact conditions. Thus, a nonlinear state error feedback and the adjustment amount of the adaptive convolutional neural network fuzzy module are combined to calculate an initial electromagnetic torque; and after the feedforward compensation, a compensated electromagnetic torque is generated and is superimposed with a torque compensation amount generated by a PI controller, thereby achieving an adaptive compensation control for dynamic load suppression of the system and effective suppression for a dynamic load impact energy of the cutting transmission system.
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