Shuttle Vehicle Positioning with Encoder Self-Correction Against Slippage
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Solution Overview
Problem
Existing shuttle vehicle systems face challenges in accurately positioning cargo due to slippage caused by heavy loads and high speeds, leading to position deviations and reduced logistics efficiency.
Innovation Solution
A shuttle vehicle traveling and positioning control method based on encoder self-correction, which uses external encoders and track positioning markers for real-time feedback and continuous error correction, achieving fully closed-loop control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the shuttle vehicle uses traditional encoder-based positioning control, then the system structure is simple, but positioning accuracy deteriorates due to slippage under heavy load and high speed
Solution Approach 1:
The patent introduces positioning markers as an intermediary element between the shuttle vehicle and the track. These markers serve as a reference medium that enables accurate position measurement without relying solely on the encoder, which is prone to slippage errors under heavy load and high speed conditions.
Solution Approach 2:
The patent replaces the purely mechanical encoder-based positioning system with an optical recognition system. By using positioning markers that can be optically detected, the system achieves higher measurement precision while reducing the reliance on mechanical components that are susceptible to slippage.
2Productivity
If the shuttle vehicle increases traveling speed and load capacity, then productivity improves, but positioning accuracy deteriorates due to increased slippage
Solution Approach 1:
The patent implements a feedback mechanism where the positioning markers provide continuous position information to the control system. This feedback allows the system to compensate for slippage errors that occur during high-speed travel and heavy load operations, maintaining positioning accuracy despite increased productivity demands.
Solution Approach 2:
The patent introduces dynamic correction capabilities by continuously comparing the expected position with the actual position detected by the positioning markers. The system dynamically adjusts for slippage errors that vary with speed and load conditions, enabling accurate positioning across a wide range of operating parameters.
3Measurement precision
If the system uses precise motion curves and closed-loop control, then positioning accuracy improves, but device complexity and cost increase
Solution Approach 1:
The patent pre-positions markers at known locations along the track, establishing a reference framework before the shuttle vehicle begins operation. This preliminary setup enables the system to achieve accurate positioning without requiring complex real-time calculations or high-performance controllers, as the reference positions are already established.
Solution Approach 2:
The patent uses simple, inexpensive positioning markers instead of complex high-performance controllers. The markers are straightforward reference elements that can be easily manufactured and installed, providing a cost-effective solution for achieving accurate positioning without requiring expensive computational hardware.
Data Source
AI summary
Disclosed in the present invention is a shuttle vehicle traveling and positioning control method based on encoder self-correction. Provided is a self-correction solution based on track positioning identifiers and external encoders. When a shuttle vehicle travels through each identifier, information is fed back and a servo target position is updated instantaneously, so as to eliminate, at any time, a cumulative error caused by skidding; and the shuttle vehicle realizes a full-closed-loop traveling and positioning control process under the guidance of position information which is corrected at any time. The shuttle vehicle traveling and positioning control method based on encoder self-correction comprises the following implementation stages: 1) performing customization and initialization; 2) performing self-learning; 3) performing self-correction; 4) updating a target position; and 5) handling a position offset.