并聯(lián)機(jī)構(gòu)位置正解的自適應(yīng)差分進(jìn)化算法
[Abstract]:According to the constraint condition of bar length, an unconstrained optimization model for solving the forward position solution of 6-DOF general 6-SPS parallel mechanism is established, and then the differential evolution (Differential evolution,DE) algorithm is applied to solve the problem. In order to improve the global optimization performance of the basic DE algorithm, an adaptive strategy is proposed to improve the global optimization performance of the algorithm, which may lead to the stagnation of evolution or fall into the region of local extremum. The adaptive differential evolution (Adaptive DE,ADE) algorithm is formed by introducing the adaptive strategy of new individuals into the DE algorithm and using hybrid mutation operator and scaling factor and cross factor based on trigonometric function disturbance to form an adaptive differential evolution (Adaptive DE,ADE) algorithm. The numerical results show that for the forward kinematics analysis of the general 6-SPS parallel mechanism, the ADE algorithm can obtain all high-precision forward position solutions with less computational overhead. Compared with the basic DE algorithm, the adaptive mutation particle swarm optimization algorithm and the improved artificial bee swarm algorithm, the convergence accuracy and computational robustness of the ADE algorithm are proved to be better than that of the contrast algorithm.
【作者單位】: 瀘州職業(yè)技術(shù)學(xué)院機(jī)械工程系;重慶工商大學(xué)制造裝備機(jī)構(gòu)設(shè)計(jì)與控制重慶市重點(diǎn)實(shí)驗(yàn)室;
【基金】:重慶市基礎(chǔ)科學(xué)與前沿技術(shù)研究專項(xiàng)(cstc2015jcyj A70006) 重慶市教育委員會(huì)科學(xué)技術(shù)研究項(xiàng)目(KJ1403201) 制造裝備機(jī)構(gòu)設(shè)計(jì)與控制重慶市重點(diǎn)實(shí)驗(yàn)室開放基金資助項(xiàng)目(611115006) 瀘州市科學(xué)技術(shù)與知識(shí)產(chǎn)權(quán)局科學(xué)技術(shù)研究項(xiàng)目(2012-S-43)
【分類號(hào)】:TH112
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