针对复合变工况下,侧倾与俯仰模式的电液馈能互联悬架(Electro-hydraulic Energy Regeneration Interconnected Suspension,EERIS)协调优化问题,设计一种包含环境选择策略的高维多目标粒子群优化算法。建立EERIS减振器阻尼力模型,通过...针对复合变工况下,侧倾与俯仰模式的电液馈能互联悬架(Electro-hydraulic Energy Regeneration Interconnected Suspension,EERIS)协调优化问题,设计一种包含环境选择策略的高维多目标粒子群优化算法。建立EERIS减振器阻尼力模型,通过试制样机进行模型试验验证并分析其参数变化在侧倾与俯仰模式下的影响规律;融合全局排序规则与全局密度估计方法,设计高维多目标粒子群优化算法;通过仿真对比EERIS优化前、单独优化侧倾模式后、单独优化俯仰模式后、协调优化侧倾与俯仰模式后的性能参数响应及均方根值。结果表明:复合变工况下,协调优化后的性能参数响应峰值降低;簧载质量加速度均方根值降低10.77%,侧倾角加速度均方根值降低24.77%,俯仰角加速度均方根值降低25.05%,提高车辆的平顺性与抗侧倾、抗俯仰能力;悬架动挠度均方根值降低7.9%,轮胎动载荷均方根值降低3.79%,车辆的操纵稳定性得到改善。展开更多
Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low ...Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.展开更多
文摘针对复合变工况下,侧倾与俯仰模式的电液馈能互联悬架(Electro-hydraulic Energy Regeneration Interconnected Suspension,EERIS)协调优化问题,设计一种包含环境选择策略的高维多目标粒子群优化算法。建立EERIS减振器阻尼力模型,通过试制样机进行模型试验验证并分析其参数变化在侧倾与俯仰模式下的影响规律;融合全局排序规则与全局密度估计方法,设计高维多目标粒子群优化算法;通过仿真对比EERIS优化前、单独优化侧倾模式后、单独优化俯仰模式后、协调优化侧倾与俯仰模式后的性能参数响应及均方根值。结果表明:复合变工况下,协调优化后的性能参数响应峰值降低;簧载质量加速度均方根值降低10.77%,侧倾角加速度均方根值降低24.77%,俯仰角加速度均方根值降低25.05%,提高车辆的平顺性与抗侧倾、抗俯仰能力;悬架动挠度均方根值降低7.9%,轮胎动载荷均方根值降低3.79%,车辆的操纵稳定性得到改善。
基金National Natural Science Foundations of China(Nos.60872073,51075068,60975017,61301219)Doctoral Fund of Ministry of Education,China(No.20110092130004)
文摘Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.
