Application of self-adaptive agent model based on sparse density and local complexity in optimization of forearm driving connecting rod of palletizing robot

Abstract

The invention discloses an application of a self-adaptive agent model based on sparse density and local complexity in optimization of a forearm driving connecting rod of a palletizing robot. Because high calculation cost is required for obtaining a real model response value in a complex engineering problem, the invention provides a self-adaptive agent model construction method based on sparse density and local complexity, and the self-adaptive agent model construction method is applied to the optimal design of the small arm driving connecting rod of the stacking robot. The method comprises thesteps: firstly, establishing a model of a stacking robot forearm driving connecting rod, and determining design variables and an optimization target; secondly, generating an initial sample, obtaininga real response, and constructing a sample library; and then, constructing an initial agent model according to the sample library, and constructing a high-precision agent model of the optimization target through the method provided by the invention; and finally, performing optimization design by using an agent model. The invention has a wide application prospect in the complex engineering optimization problem and under the condition that the target function is difficult to obtain.

Description

technical field [0001] The invention belongs to the technical field of engineering design, and in particular relates to the application of an adaptive proxy model based on density and local complexity in the optimization of the small arm drive link of a palletizing robot. Background technique [0002] In complex engineering problems, how to obtain the response value of the real model is often a difficult problem, and it is faced with the problem of high computational cost when analyzing by establishing a high-precision simulation model. The emergence of proxy model technology has effectively alleviated this situation. The proxy model generally refers to an approximate mathematical model that after sampling the design space, the amount of calculation established is much smaller than the original model, and the calculation accuracy is close to the original model. Commonly used surrogate models include: polynomial response surface, radial basis function, Kriging, artificial neu...

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Problems solved by technology

At present, the method of obtaining the maximum stress and maximum displacement of the current design point in optimization is a large-scale computer simulation experiment, which is very time-consuming

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