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收割机作业速度多目标控制模型的鲁棒优化设计
引用本文:王 新,付 函,王书茂,崔志英,程丽霞.收割机作业速度多目标控制模型的鲁棒优化设计[J].农业工程学报,2012,28(20):27-33.
作者姓名:王 新  付 函  王书茂  崔志英  程丽霞
作者单位:1. 中国农业大学工学院,北京 100083
2. 中机北方机械有限公司,长春 130507
基金项目:国家十二五科技支撑项目(2011BAD20B04)
摘    要:本文围绕稻麦联合收割机作业速度控制策略问题,以收割机作业质量、作业效率、能效利用率为控制目标,基于模型鲁棒优化理论,建立了基于多目标控制的收割机作业速度控制模型;在分析各控制目标约束条件和满足收获损失率、作业效率和能效系数期望区间的基础上,考虑控制目标对田间作业参数变化的灵敏度,提出一种基于模拟退火算法的控制目标权重因子优化方法。田间试验结果表明,当草谷比变化率为40%,谷物密度变化率为29.9%时,本控制模型可将收获损失率控制在0.42%~0.43%范围内,脱粒滚筒功耗15.12~16.99kW,并能实现收割机复杂工作环境下作业速度的合理控制,进一步验证了控制模型的鲁棒性和可行性。

关 键 词:收割机  鲁棒性  多目标优化  作业速度  模拟退火算法
收稿时间:2012/6/13 0:00:00
修稿时间:2012/9/19 0:00:00

Robust optimal design of multi-objective control model of working speed for combine harvester
Wang Xin,Fu Han,Wang Shumao,Cui Zhiying and Cheng Lixia.Robust optimal design of multi-objective control model of working speed for combine harvester[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(20):27-33.
Authors:Wang Xin  Fu Han  Wang Shumao  Cui Zhiying and Cheng Lixia
Institution:1 (1. College of Engineering, China Agricultural University, Beijing 100083, China; 2. China Northern Machinery Co.,Ltd, Changchun 130507, China)
Abstract:In this paper, the working speed control strategy of combine harvester was studied. Taking harvest loss, harvest efficiency and energy cost as multiply control targets, the multiple targets working speed control model was built based on robust optimization theory. Considering the analysis of the constraint conditions, expected space of control targets and the consideration of sensitivity of control target to the parameter variation, annealing algorithm was proposed to calculate the weighting factor of the control targets and applied to the control parameter of harvest speed. Field testing showed the multiple targets control model can make the grain loss in the range from 0.42%-0.43% and threshing power consumption can be controlled from 15.12 to 17.32 kW when the deviation rate of straw-grain ratio and grain density were 40% and 29.9%. It showed that with this control model rational control of harvest speed can be achieved even under the harsh working condition, and verified the robustness and validity of the control model.
Keywords:harvesters  robustness  multiple objective optimization  harvest speed  simulated annealing algorithm
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