H∞ filtering for discrete-time systems subject to stochastic missing measurements: a decomposition approach

This paper deals with the problem of H_∞ filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment is governed by its corresponding random variables. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square with a less conservatism while the disturbance rejection attenuation is constrained to a given level by means of an H_∞ performance index. Based on Lyapunov theory, the reliable filter parameters are characterised in terms of the feasibility of a set of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.     

Stability analysis and controller synthesis for discrete uncertain singular fuzzy systems with distinct difference matrices in the rules

This paper mainly studies an extended discrete singular fuzzy model incorporating the multiple difference matrices in the rules and discusses its stability and design issues. By embracing additional algebraic constraint, traditional discrete Takagi-Sugeno (T-S) fuzzy model can be extended to a generalised discrete singular Takagi-Sugeno (GDST-S) model with individual difference matrices E_i in the locally singular models, where it can describe a larger class of physical or non-linear systems. Based on the linear matrix inequality (LMI) approach, we focus on deriving some explicit stability and design criteria expressed by the LMIs for the regarded system. Thus, the stability verification and controller synthesis can be performed by the current LMI tools. Finally, some illustrative examples are given to illustrate the effectiveness and validity of the proposed approach.     

Sliding mode control for Markov jump linear uncertain systems with partly unknown transition rates

In this paper, based on sliding mode control approach, the robust stabilisation problem for a class of continuous-time Markovian jump linear uncertain systems with partly unknown transition rates is investigated. The transition rate matrix under consideration covers completely known, boundary known and completely unknown elements. By making use of linear matrix inequalities technique, sufficient conditions are presented to derive the linear switching surface and guarantee the stochastic stability of sliding mode dynamics. Then a sliding mode control law is designed to drive the state trajectory of the closed-loop system to the specified linear switching surface in finite time in spite of the existing uncertainties and unknown transition rates. Finally, an example is given to verify the validity of the theoretical results.     

Integrated Fisher linear discriminants: An empirical study

This paper studies Fisher linear discriminants (FLDs) based on classification accuracies for imbalanced datasets. An optimal threshold is found out from a series of empirical formulas developed, which is related not only to sample sizes but also to distribution regions. A mixed binary–decimal coding system is suggested to make the very dense datasets sparse and enlarge the class margins on condition that the neighborhood relationships of samples are nearly preserved. The within-class scatter matrices being or approximately singular should be moderately reduced in dimensionality but not added with tiny perturbations. The weight vectors can be further updated by a kind of epoch-limited (three at most) iterative learning strategy provided that the current training error rates come down accordingly. Putting the above ideas together, this paper proposes a type of integrated FLDs. The extensive experimental results over real-world datasets have demonstrated that the integrated FLDs have obvious advantages over the conventional FLDs in the aspects of learning and generalization performances for the imbalanced datasets.     

丙烯酸接枝线形低密度聚乙烯的热学行为及结晶形态

利用差示扫描量热仪研究了丙烯酸接枝线形低密度聚乙烯（PE-LLD-g-AA）的热学行为，结果表明，与纯线形低密度聚乙烯（PE—LLD）相比，PE-LLD-g-AA的熔融温度（Tm）略有增加，结晶温度（Tc）增加大约4℃，熔融焓（AHm）随AA含量的增加而降低。还利用差示扫描量热仪研究了PE—LLD和PE—LLD-g—AA的等温结晶动力学，用扫描电子显微镜观察了PE—LLD-g—AA等温结晶形态。结果表明，PE-LLD-g-AA的结晶速率大于纯PE—LLD的，随着接枝率的增加，PE-LLD的球晶半径减小，接枝到PE—LLD分子链上的AA分子起到了成核剂的作用。     

On control of discrete-time state-dependent jump linear systems with probabilistic constraints: A receding horizon approach

In this article, we consider a receding horizon control of discrete-time state-dependent jump linear systems, a particular kind of stochastic switching systems, subject to possibly unbounded random disturbances and probabilistic state constraints. Due to the nature of the dynamical system and the constraints, we consider a one-step receding horizon. Using inverse cumulative distribution function, we convert the probabilistic state constraints to deterministic constraints, and obtain a tractable deterministic receding horizon control problem. We consider the receding horizon control law to have a linear state-feedback and an admissible offset term. We ensure mean square boundedness of the state variable via solving linear matrix inequalities off-line, and solve the receding horizon control problem on-line with control offset terms. We illustrate the overall approach applied on a macroeconomic system.     

MCM-22沸石催化剂的苯与长链烯烃烷基化性能

用NH3-TPD法研究了4种不同硅铝摩尔比的MCM-22沸石的酸性质,在常压间歇式反应器中考察了它们在苯与长链烯烃烷基化反应中的催化性能,并与HY和HZSM-5沸石催化剂进行了比较。实验结果发现MCM-22的催化活性与其强酸量有一致的关系,与其硅铝摩尔比无对应关系;MCM-22的活性比HY低,但对2-P的选择性远远高于HY,这说明了MCM-22对2-P具有形状选择作用。     

大规模水电系统优化调度降维方法研究I:理论分析

中国水电系统规模持续扩张,使得已有方法在求解大规模水电调度问题时,存在严重维数灾及早熟收敛等不同程度局限,亟需分析已有方法以便发现其瓶颈所在,为探寻能均衡求解效率与计算精度的实用化方法提供有益参考。为此,首先深入研究了线性规划、二次规划和动态规划等多种方法的计算复杂度,然后定量对比分析了各方法在不同情景下的适用性,最后提出“四维一体可拓降维”总体思想,并给出具体的降维方法与策略,建议从空间维、时间维、状态维和组合维等4个方面开展综合研究,以切实服务于大规模水电系统优化调度的高效优质求解。     

Monitoring the linear alkylbenzene sulfonation process using high-temperature gas chromatography

Controlling the linear alkylbenzene sulfonate (LAS) sulfonation process is a critical part of the LAS manufacturing process; this process can be monitored by assaying for LAS content, unsulfonated linear alkylbenzene (LAB), and LAB sulfones. Traditionally, assaying the LAB and LAB sulfone contents has been time consuming and not straightforward. A simple and rapid procedure is described for the isolation and simultaneous capillary gas chromatographic (GC) quantification of LAB and LAB sulfones in LAS. The procedure involves extraction of the unsulfonated LAB and the LAB sulfones into n-heptane; sodium linear alkylbenzenesulfonate or linear alkylbenzenesulfonic acid (reacted to form sodium linear alkylbenzenesulfonate) remains in the aqueous extraction solvent layer. High-temperature capillary GC using a specialty metal capillary column enables both LAB and high molecular weight LAB sulfones to be quantified.