An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

混菌矿化增强再生粗骨料的物理力学性能

为克服单一微生物培养成本高且矿化鲁棒性不足的缺陷，提出了一种混菌矿化增强再生粗骨料物理力学性能的方法.通过筛选矿化效率较高的好氧嗜碱混菌，考察了混菌矿化对再生粗骨料物理力学性能和混凝土抗压强度的影响.结果表明：相同增强时间下，混菌比纯菌呈现出更优异的矿化增强效果；随着混菌矿化增强时间的延长，再生粗骨料吸水率和压碎指标呈现出先减小后增大的趋势，最优增强时间为15 d；采用矿化增强再生粗骨料制备的再生混凝土抗压强度提高幅度达到22.1%.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

日本优良食味稻米灌浆期水管理、鲜谷干燥温度及糙米水分与食味关系研究（译文）

为了生产优良食味稻米,克服栽培环境的影响非常重要。主要论述了灌浆期最适宜的用水管理、新鲜稻谷的干燥温度以及糙米水分含量与其食味之间的关系。水稻灌浆期最适宜的用水管理是湿润管理法,通过对灌浆期水稻的湿润管理,可有效抑制水田土壤温度上升,保持根系活力,提高稻米结实率,最终实现稻米增收与食味提升。新鲜稻谷水分含量不同,干燥所需的送风温度也不同,22%、25%、30%的水分含量分别对应的适宜温度为55、48、35℃。糙米中14%～15%的水分含量能够保证稻米的最佳食味。     

Various density light field image coding based on distortion minimization interpolation

In recent years, the light field (LF) as a new imaging modality has attracted wide interest. The large data volume of LF images poses great challenge to LF image coding, and the LF images captured by different devices show significant differences in angular domain. In this paper we propose a view prediction framework to handle LF image coding with various sampling density. All LF images are represented as view arrays. We first partition the views into reference view (RV) set and intermediate view (IV) set. The RVs are rearranged into a pseudo sequence and directly compressed by a video encoder. Other views are then predicted by the RVs. To exploit the four dimensional signal structure, we propose the linear approximation prior (LAP) to reveal the correlation among LF views and efficiently remove the LF data redundancy. Based on the LAP, a distortion minimization interpolation (DMI) method is used to predict IVs. To robustly handle the LF images with different sampling density, we propose an Iteratively Updating depth image based rendering (IU-DIBR) method to extend our DMI. Some auxiliary views are generated to cover the target region and then the DMI calculates reconstruction coefficients for the IVs. Different view partition patterns are also explored. Extensive experiments on different types LF images also valid the efficiency of the proposed method.     

马尔可夫跳变线性系统最优控制的研究现状与进展

马尔可夫跳变线性系统（MJLS）是一种具有多个模态的随机系统，系统在各个模态之间的跳变转移由一组马尔可夫链来决定。MJLS模型因其在表示过程中可以产生突变而更能精确的描述实际工程应用中的系统。近年来，MJLS的最优控制问题成为了研究的热点，动态规划、极大值原理以及线性矩阵不等式等成为了解决此类问题的主流方法。本文对MJLS最优控制领域的研究现状进行了综述。分别对一般情况下、带有噪声的情况下、带有时滞的情况下以及某些特定情况下的MLJS最优控制问题的国内外研究现状进行论述。最后进行了总结并提出MJLS最优控制领域未来值得关注的研究方向。     

基于拼接缝自适应消除和全景图矫直的快速图像拼接算法

针对图像拼接存在色差过渡不均匀、图像倾斜扭曲及拼接效率低的现象，提出一种基于拼接缝自适应消除和全景图矫直的快速图像拼接算法。首先，用尺度不变特征变换（SIFT）提取图像指定区域特征点并用双向K近邻（KNN）算法进行图像配准，有效提高算法效率；其次，利用动态规划思想提出自适应公式找到最优拼接缝并用图像融合算法对其自适应消除，解决拼接缝色差过渡不均匀问题；最后，针对累积拼接误差形成全景图倾斜的现象，利用边缘检测算法提出自适应拟合四边形矫直模型，把原始全景图矫直为一个全新的全景图。所提算法与分块图像拼接和二叉树图像拼接算法相比，图像质量提升了5.84%~7.83%，拼接时间仅为原来的50%~70%。实验结果表明，该算法不仅通过自适应更新机制减少不同图像背景下拼接缝色差过渡不均匀的现象，从而提高了图像质量；而且提高了拼接效率，降低了全景图倾斜扭曲程度。