Optimization design of drive system for industrial robots based on dynamic performance

Abstract

Purpose

The global performance of industrial robots partly depends on the properties of drive system consisting of motor inertia, gearbox inertia, etc. This paper aims to deal with the problem of optimization of global dynamic performance for robotic drive system selected from available components.

Design/methodology/approach

Considering the performance specifications of drive system, an optimization model whose objective function is composed of working efficiency and natural frequency of robots is proposed. Meanwhile, constraints including the rated and peak torque of motor, lifetime of gearbox and light-weight were taken into account. Furthermore, the mapping relationship between discrete optimal design variables and component properties of drive system were presented. The optimization problem with mixed integer variables was solved by a mixed integer-laplace crossover power mutation algorithm.

Findings

The optimization results show that our optimization model and methods are applicable, and the performances are also greatly promoted without sacrificing any constraints of drive system. Besides, the model fits the overall performance well with respect to light-weight ratio, safety, cost reduction and others.

Practical implications

The proposed drive system optimization method has been used for a 4-DOF palletizing robot, which has been largely manufactured in a factory.

Originality/value

This paper focuses on how the simulation-based optimization can be used for the purpose of generating trade-offs between cost, performance and lifetime when designing robotic drive system. An applicable optimization model and method are proposed to handle the dynamic performance optimization problem of a drive system for industrial robot.

Citation

Ge, L., Chen, J., Li, R. and Liang, P. (2017), "Optimization design of drive system for industrial robots based on dynamic performance", Industrial Robot, Vol. 44 No. 6, pp. 765-775. https://doi.org/10.1108/IR-10-2016-0251