Finite Series Approximation for Stacker Crane Memory Optimization
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Solution Overview
Problem
The existing memory capacity in automated guided vehicles is insufficient to store the large amount of dot-sequential data required for optimal speed patterns, which are necessary to control vibration and vary with distance and position, leading to increased memory requirements.
Innovation Solution
Deriving a finite series approximation of the dot-sequential data, specifically using a Fourier series with a finite number of terms, to reduce the data storage needs and allow for efficient reproduction of the pattern, while also identifying key coefficients and frequencies that impact the pattern's reproduction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dot-sequential data indicating temporal variation in position, speed, or acceleration is stored in memory as it is, then the speed pattern can be accurately reproduced for vibration control, but the memory capacity becomes insufficient and needs to be increased
Solution Approach 1:
The patent applies the copying principle by replacing the original dot-sequential data with a copied representation in the form of curve function data. Instead of storing the actual speed pattern data points, the system stores mathematical function data that can reproduce the same speed pattern. This copying approach significantly reduces memory capacity requirements while maintaining the ability to accurately reproduce the speed pattern for vibration control during automated guided vehicle operation.
2Adaptability or versatility
If many dot-sequential data are stored to accommodate different running distances, then the automated guided vehicle can run different distances, but the amount of data to be stored increases further
Solution Approach 1:
The patent applies the dynamics principle by making the speed pattern adaptable through mathematical functions rather than static data storage. The curve function data stored in memory can dynamically generate speed patterns for different running distances by adjusting parameters such as the number of cycles and time constants. This allows the same set of function data to serve multiple running distance requirements, providing flexibility without proportionally increasing storage requirements.
3Quantity of substance
If the memory capacity is increased to store dot-sequential data, then the proper storage can be achieved, but the device complexity and cost increase
Solution Approach 1:
The patent applies the copying principle by replacing the original dot-sequential data with a copied representation in the form of curve function data. Instead of storing the actual speed pattern data points, the system stores mathematical function data that can reproduce the same speed pattern. This copying approach significantly reduces memory capacity requirements while maintaining the ability to accurately reproduce the speed pattern for vibration control during automated guided vehicle operation.
Data Source
AI summary
When dot-sequential data indicating a temporal variation in position, speed, or acceleration is stored in a memory in an automated guided vehicle as it is, the capacity of the memory is insufficient and thus needs to be increased. A pattern is mounted in a stacker crane 1; the pattern is drawn by dot-sequential data indicating a temporal variation in acceleration (FIG. 2C), and corresponds to an instruction value provided to an actuator installed in the stacker crane 1. In this case, a curve function corresponding to an approximate expression for the dot-sequential data is derived in a form of a Fourier series having a finite number of terms and using time as an independent variable and the position, speed, or acceleration as a dependent variable. Data identifying the Fourier series, having a finite number of terms, is stored in a memory 5 mounted in the stacker crane 1.