Peristaltic pump control method for pneumatic mechanical gripper

By dynamically tuning the parameters of the peristaltic pump PID controller using an adaptive migration optimization algorithm, the fluctuation and lag problems in the control process of the pneumatic manipulator are solved, achieving higher control stability and accuracy, and making it suitable for micro-angle operation of the pneumatic manipulator.

CN121552403AActive Publication Date: 2026-02-24BEIHUA UNIV
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Patent Information

Application Number
CN202610076628.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-21
Publication Date
2026-02-24
Estimated Expiration
2046-01-21

AI Technical Summary

Technical Problem

Existing pneumatic manipulator control systems suffer from problems such as large control fluctuations, slow response, reliance on human experience for parameter tuning, and difficulty in adapting to complex operating scenarios.

Method used

An adaptive migration optimization algorithm is used to dynamically optimize and tune the parameters of the peristaltic pump PID controller. Combined with pneumatic conversion modeling and historical response offset correction mechanism, a closed-loop control link is constructed to achieve precise control of the peristaltic pump.

Benefits of technology

It significantly improves the control stability and precision of pneumatic manipulators, enhances robustness to nonlinear disturbances, ensures the accuracy of bending angles and response speed, and is suitable for precise micro-angle operation of pneumatic manipulators.

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Abstract

The invention provides a peristaltic pump control method for a pneumatic mechanical gripper, which relates to the field of intelligent control, and comprises the following steps: constructing a pneumatic conversion module, a peristaltic pump PID control module, a driving execution module, a bending sensing module and an error feedback processing module; the bending angle difference of the mechanical gripper is calculated and subjected to pneumatic conversion to obtain a bending error; the position type PID outputs a control signal, and Kp, Ki and Kd are set on line through a self-adaptive migration optimization algorithm; adjusting and updating individuals by utilizing a direction perception consensus index, a virtual adsorption point set and an adsorption step length; generating a time offset factor correction time sequence based on the historical response memory function; and the corrected signal drives a motor, and precise control over the mechanical gripper is achieved. According to the method, overshoot and steady-state errors are remarkably reduced, response time is shortened, oscillation is suppressed, manual parameter adjustment is reduced, and robustness is improved.
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