A programmable logic control system for a handling robot work flow

By introducing a monitoring mechanism for topological stiffness and spatiotemporal misalignment deviation in a high-density automated storage and retrieval system, and combining a dynamic potential energy field model and multi-agent deep learning, adaptive control is achieved, solving the system deadlock problem caused by physical space congestion and communication interference, and improving the system's resilience and operating efficiency.

CN122363017APending Publication Date: 2026-07-10STATE GRID GANSU ELECTRIC POWER CO LANZHOU POWER SUPPLY CO
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
STATE GRID GANSU ELECTRIC POWER CO LANZHOU POWER SUPPLY CO
Filing Date
2026-03-13
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing programmable logic control systems are unable to effectively cope with the complex working conditions of physical space congestion and wireless communication interference in high-density automated warehouses, leading to the risk of system deadlock and system paralysis.

Method used

A dual monitoring mechanism for topological stiffness and spatiotemporal misalignment is introduced. By constructing a dynamic potential energy field model and a Kalman filter model, combined with a multi-agent deep reinforcement learning model, adaptive mode switching is achieved to avoid the risk of deadlock.

Benefits of technology

By identifying critical combinations of high network stiffness and high communication delay in advance under communication interference, an unrecoverable full-field deadlock state can be avoided, thereby improving system resilience and efficiency.

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Abstract

This invention provides a programmable logic control system for the operation process of a handling robot, relating to the fields of robot control and intelligent logistics technology. It includes a data acquisition module for acquiring the operating characteristics of the mobile work unit and channel state parameters; a topology analysis module for constructing a dynamic potential energy field model and calculating the topology stiffness coefficient; an interference assessment module for calculating the spatiotemporal misalignment deviation value based on the channel packet loss rate and command response timestamps; a logic decision module for determining the deadlock risk level based on the topology stiffness coefficient and the spatiotemporal misalignment deviation value; and an adaptive control module for generating operating mode switching commands based on the deadlock risk level to switch between efficiency-oriented and survival-oriented modes. This invention effectively avoids a full-field deadlock caused by asynchrony between cyber-physical systems through a dual monitoring mechanism.
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