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。
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.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2012年第20期27-33,共7页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家十二五科技支撑项目(2011BAD20B04)
关键词
收割机
鲁棒性
多目标优化
作业速度
模拟退火算法
harvesters, robustness, multiple objective optimization, harvest speed, simulated annealing algorithm
