Torpedo ladle positioning control method based on fuzzy neural network and inertia compensation

The torpedo can positioning control method using fuzzy neural networks and inertial compensation adjusts the response and deceleration time in real time, solving the problem of insufficient accuracy caused by delay and changes in operating conditions in traditional torpedo can positioning control, and achieving high-precision and stable torpedo can positioning.

CN122449912AActive Publication Date: 2026-07-24HUBEI COMMUNICATIONS CONSTRUCTION JINGTIAN PREFABRICATED CONSTRUCTION CO LTD
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Patent Information

Application Number
CN202610197552.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-11
Publication Date
2026-07-24
Estimated Expiration
2046-02-11

AI Technical Summary

Technical Problem

Traditional torpedo canister positioning control methods cannot effectively handle control signal transmission delays, mechanical braking response delays, and complex operating condition changes, resulting in insufficient positioning accuracy and difficulty in meeting the alignment accuracy and system stability requirements of modern industry.

Method used

A control method based on fuzzy neural network and inertial compensation is adopted. By collecting the actual stopping position and preset target position of the torpedo tank in real time, the positioning deviation is calculated. Based on the TS fuzzy neural network, the correction coefficients of response time and deceleration time are dynamically adjusted. Combined with the inertial compensation model, the braking trigger position is accurately determined to achieve high-precision positioning.

Benefits of technology

Achieve high-precision positioning within ±5cm under complex working conditions, reduce mechanical structural impact, improve production efficiency, adapt to various working condition changes, and meet the needs of automated production.

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Abstract

The invention provides a torpedo ladle positioning control method based on a fuzzy neural network and inertia compensation, and the method comprises the steps: building an inertia compensation model, taking the total response time of a braking system as a key parameter, calculating and compensating the inertia displacement in advance, and precisely determining a braking triggering position; meanwhile, an improved T-S fuzzy neural network is introduced to construct dynamic mapping of working condition parameters and correction coefficients, and online self-learning and self-adaptive adjustment of positioning parameters are achieved. According to the scheme, systematic deviation can be effectively eliminated, it is ensured that the torpedo ladle can maintain the positioning precision within + / -5 cm in various complex scenes, and impact on a mechanical structure is remarkably reduced while the production efficiency is improved.
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