Kinematics uncertainty analysis of mine bolter manipulator based on Chebyshev interval algorithms

Jun Zhang,Wenjun Meng,Xiangdong Yu,Guoying Meng,Lifeng Ma,Qing-Xue Huang

doi:10.1177/1687814019849329

Abstract

A mine bolter is a fast, safe and economical support equipment, in which the manipulator is the key component for its parallel operation. In this study, the kinematics of mine bolter manipulator is selected as the research object. Aiming at the problem of the dynamic system response estimation of positive solution matrix with uncertain parameters, an interval estimation analysis method based on Chebyshev polynomial is proposed. The response envelope interval of the forward kinematics solution matrix of the manipulator with uncertain parameters is investigated using three types of surrogate models: scanning method, tensor product and collocation method. The feasibility and efficiency of the proposed algorithm are proved by a prototype test. The study of response interval with uncertain parameters has become a new method for predicting the spatial trajectory tracking and location of the manipulator to ensure that its prediction error is minimal.

Highlights

To meet the needs of coal enterprises for bolt support speed, operation safety, people reduction and increased efficiency, research and development of a mine bolter were conducted to track the international advanced level of support equipment
The Chebyshev expansion function is constructed by using the Chebyshev polynomial coefficients obtained from the process, and the dynamic response interval is acquired
The results of collocation method (CCM) and SAS are close to the theoretical values

Summary

Introduction

To meet the needs of coal enterprises for bolt support speed, operation safety, people reduction and increased efficiency, research and development of a mine bolter were conducted to track the international advanced level of support equipment. L Wang et al.[7] applied the extreme learning machine algorithm to the mathematical model of the research object They used the spatial network sampling method to analyse the variation law of errors. X Hou et al.[10] applied simulation and experiment methods to simulate the study object in ADAMS environment They analysed the dynamic errors caused by variable load, improved the positioning accuracy of robots and designed and developed an error compensation interface for human–computer interaction. On the basis of Chebyshev expansion function theory, our study performs the uncertainty error analysis of the kinematics of mine bolter manipulators by combining scanning method (SAS), collocation method (CCM) and tensor product (CTP) proxy models.

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Findings

Method