2009•Unpublished venueRequires access

Multidisciplinary collaborative optimization design of robots

Jing Zhang, Bailin Li, Yongjun Liu

Abstract

The idea of multidisciplinary design optimization (MDO) is applied to synthesize optimum robots. The main idea and frame of collaborative optimization are introduced. Three disciplines of working stroke L driving performance and hydraulic component are involved in the design optimization of a 3-RRS robot. The optimization model of system-level and optimization model of subsystem are established. Sequential quadratic programming (SQP) and genetic algorithm (GA) are respectively used to execute the optimization of system-level and the optimization of subsystems using popular commercialized MATLAB. The numerical results indicate that the collaborative optimization can be successfully applied to dealing with the complex robot system, and lay a foundation to solve more complex mechanical system. (5 pages)

About this research paper

What this paper is about

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: Multidisciplinary design optimization, Sequential quadratic programming, Robot, Computer science, Component (thermodynamics), MATLAB, Engineering optimization, Frame (networking)