Improved exponential observer design for one‐sided Lipschitz nonlinear systems

This paper investigates the exponential observer design problem for one‐sided Lipschitz nonlinear systems. A unified framework for designing both full‐order and reduced‐order exponential state observers is proposed. The developed design approach requires neither scaling of the one‐sided Lipschitz constant nor the additional quadratically inner‐bounded condition. It is shown that the synthesis conditions established include some known existing results as special cases and can reduce the intrinsic conservatism. For design purposes, we also formulate the observer synthesis conditions in a tractable LMI form or a Riccati‐type inequality with equality constraints. Simulation results on a numerical example are given to illustrate the advantages and effectiveness of the proposed design scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

An analysis of the exponential stability of linear stochastic neutral delay systems

This paper is concerned with the analysis of the mean square exponential stability and the almost sure exponential stability of linear stochastic neutral delay systems. A general stability result on the mean square and almost sure exponential stability of such systems is established. Based on this stability result, the delay partitioning technique is adopted to obtain a delay‐dependent stability condition in terms of linear matrix inequalities (LMIs). In obtaining these LMIs, some basic rules of the Ito calculus are also utilized to introduce slack matrices so as to further reduce conservatism. Some numerical examples borrowed from the literature are used to show that, as the number of the partitioning intervals increases, the allowable delay determined by the proposed LMI condition approaches h_max, the maximal allowable delay for the stability of the considered system, indicating the effectiveness of the proposed stability analysis. Copyright © 2013 John Wiley & Sons, Ltd.     

Exponential stability of stochastic singular delay systems with general Markovian switchings

In recent years, Markovian jump systems have received much attention. However, there are very few results on the stability of stochastic singular systems with Markovian switching. In this paper, the discussed system is the stochastic singular delay system with general transition rate matrix in terms of uncertain and partially unknown transition rate matrix. The aim is to answer the question whether there are conditions guaranteeing the underlying system having a unique solution and being exponentially admissible simultaneously. The proposed results show that all the features of the underlying system such as time delay, diffusion, and general Markovian switchings play important roles in the system analysis of exponential admissibility. A numerical example is used to demonstrate the effectiveness of the proposed methods. Copyright © 2014 John Wiley & Sons, Ltd.     

Chaotic bat swarm optimisation (CBSO)

Bat swarm optimisation (BSO) is a novel heuristic optimisation algorithm that is being used for solving different global optimisation problems. The paramount problem in BSO is that it severely suffers from premature convergence problem, that is, BSO is easily trapped in local optima. In this paper, chaotic-based strategies are incorporated into BSO to mitigate this problem. Ergodicity and non-repetitious nature of chaotic functions can diversify the bats and mitigate premature convergence problem. Eleven different chaotic map functions along with various chaotic BSO strategies are investigated experimentally and the best one is chosen as the suitable chaotic strategy for BSO. The results of applying the proposed chaotic BSO to different benchmark functions vividly show that premature convergence problem has been mitigated efficiently. Actually, chaotic-based BSO significantly outperforms conventional BSO, cuckoo search optimisation (CSO), big bang-big crunch algorithm (BBBC), gravitational search algorithm (GSA) and genetic algorithm (GA).     

Particle swarm algorithm with adaptive constraint handling and integrated surrogate model for the management of petroleum fields

This paper deals with the development of effective techniques to automatically obtain the optimum management of petroleum fields aiming to increase the oil production during a given concession period of exploration. The optimization formulations of such a problem turn out to be highly multimodal, and may involve constraints. In this paper, we develop a robust particle swarm algorithm coupled with a novel adaptive constraint-handling technique to search for the global optimum of these formulations. However, this is a population-based method, which therefore requires a high number of evaluations of an objective function. Since the performance evaluation of a given management scheme requires a computationally expensive high-fidelity simulation, it is not practicable to use it directly to guide the search. In order to overcome this drawback, a Kriging surrogate model is used, which is trained offline via evaluations of a High-Fidelity simulator on a number of sample points. The optimizer then seeks the optimum of the surrogate model.     

Stability Analysis for Delayed Neural Networks with Discontinuous Neuron Activations

This paper considers a class of delayed neural networks with discontinuous neuron activations. Based on the theory of differential equations with discontinuous right‐hand sides, some novel sufficient conditions are derived that ensure the existence and global exponential stability of the equilibrium point. Moreover, by adopting the concept of convergence in measure, convergence behavior for the output is discussed. The obtained results are independent of the delay parameter and can be thought of as a generalization of previous results established for delayed neural networks with Lipschtz continuous neuron activations to the discontinuous case. Finally, we give a numerical example to illustrate the effectiveness and novelty of our results by comparing our results with those in the early literature.     

PLC在机房环境监控系统中的应用

基于PLC设计了一套机房环境监控系统,系统可监测机房环境、UPS运行状态、智能空调运行状态。系统可通过GSM短信息的方式将异常情况及时通知工作人员,实现机房的无人职守。     

基于融合信息的癌症相关基因选择方法

基因表达数据的出现,为人类从分子生物学的角度研究和探索癌症的发病机理提供了广阔的前景,利用基因表达数据发现与癌症相关的基因对于癌症的诊断和治疗具有重要的意义。在过去的十几年里,已经有很多种计算方法被成功地用于从基因表达数据中找出与癌症相关的关键基因,然而,不同的方法从不同的角度刻画基因对不同类型样本的区分能力,它们选择出来的关键基因可能不一致,这将给医学解释和应用带来困扰。现提出一种融合的方法,即将基因在不同方面对样本的判别能力结合起来,首先计算每个基因的信息增益、全局判别能力和局部判别能力,再用它们的识别率进行加权,进而计算每个基因的综合判别能力,最后筛选出判别能力最高的基因子集作为关键基因子集。实验结果表明,此方法得到了比采用单独一种评价标准更好的识别效果。     

基于模式搜索的连续函数寻优

模式搜索方法是求解最优化问题的一种直接搜索方法,它只根据函数值信息来进行求优。但模式搜索对起始点非常敏感,对好的起始点,模式搜索可以搜索到全局最优点,但对某些起始点,模式搜索只能搜索到局部极值点。本文提出基于模式搜索的一个新方法,实验证明,它能搜索到全局最优。     

Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets

Many investigators need and use global land cover maps for a wide variety of purposes. Ironically, after many years of very limited availability, there are now multiple global land cover maps and it is not readily apparent (1) which is most useful for particular applications or (2) how to combine the different maps to provide an improved dataset. The existing global land cover maps at 1 km spatial resolution have arisen from different initiatives and are based on different remote sensing data and employed different methodologies. Perhaps more significantly, they have different legends. As a result, comparison of the different land cover maps is difficult and information about their relative utility is limited. In an attempt to compare the datasets and assess their strengths and weaknesses we harmonized the thematic legends of four available coarse-resolution global land cover maps (IGBP DISCover, UMD, MODIS 1-km, and GLC2000) using the LCCS-based land cover legend translation protocols. Analysis of the agreement among the global land cover maps and existing validation information highlights general patterns of agreement, inconsistencies and uncertainties. The thematic classes of Evergreen broadleaf trees, Snow and Ice, and Barren show high producer and user accuracy and good agreement among the datasets, while classes of mixed tree types show high commission errors. Overall, the results show a limited ability of the four global products to discriminate mixed classes characterized by a mosaic of trees, shrubs, and herbaceous vegetation. There is a strong relationship between class accuracy, spatial agreement among the datasets, and the heterogeneity of landscapes. Suggestions for future mapping projects include careful definition of mixed unit classes, and improvement in mapping heterogeneous landscapes.