Comparative Analysis of Optimization Algorithms in Workspace Optimization of Parallel Mechanisms

Abstract

Abstract: Large workspace is an important target in parallel mechanism design. The application of three optimization algorithms in the workspace optimization of parallel mechanisms is studied by taking a 6-RSS parallel mechanism of 6 DOFs as example. The optimization model is established. Then the performances of the optimization algorithms are analyzed and compared, and the main investigated performance indexes are optimization results, numerical stability and time efficiency. The optimization algorithms concerned are multi-island genetic algorithm (MIGA), generalized reduced gradient method and sequential quadratic programming method, and the latter two in application are respectively integrated with design of experiment (DOE) method. The experimental analysis shows that local optimization algorithms integrated with DOE has obvious advantage that the workspace volume of the 6-RSS parallel mechanism increases to 2.59 times that of the original one, the time taken for optimization is only 1/5 that of MIGA, and the optimization result is stable.

Key words: Design of experiment, Numerical stability, Optimization algorithm, Parallel mechanism, Time efficiency, Workspace

CLC Number:

TP242

LI Hao;ZHANG Yuru;WANG Dangxiao. Comparative Analysis of Optimization Algorithms in Workspace Optimization of Parallel Mechanisms[J]. , 2010, 46(13): 61-67.

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http://www.cjmenet.com.cn/EN/Y2010/V46/I13/61

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Comparative Analysis of Optimization Algorithms in Workspace Optimization of Parallel Mechanisms

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