Stability analysis for discrete delayed Markovian jumping neural networks with partly unknown transition probabilities

This paper addresses the analysis problem of asymptotic stability for a class of uncertain neural networks with Markovian jumping parameters and time delays. The considered transition probabilities are assumed to be partially unknown. The parameter uncertainties are considered to be norm-bounded. A sufficient condition for the stability of the addressed neural networks is derived, which is expressed in terms of a set of linear matrix inequalities. A numerical example is given to verify the effectiveness of the developed results.     

Components meet aspects: Assessing design stability of a software product line

Context

It is important for Product Line Architectures (PLA) to remain stable accommodating evolutionary changes of stakeholder’s requirements. Otherwise, architectural modifications may have to be propagated to products of a product line, thereby increasing maintenance costs. A key challenge is that several features are likely to exert a crosscutting impact on the PLA decomposition, thereby making it more difficult to preserve its stability in the presence of changes. Some researchers claim that the use of aspects can ameliorate instabilities caused by changes in crosscutting features. Hence, it is important to understand which aspect-oriented (AO) and non-aspect-oriented techniques better cope with PLA stability through evolution.

Objective

This paper evaluates the positive and negative change impact of component and aspect based design on PLAs. The objective of the evaluation is to assess how aspects and components promote PLA stability in the presence of various types of evolutionary change. To support a broader analysis, we also evaluate the PLA stability of a hybrid approach (i.e. combined use of aspects and components) against the isolated use of component-based, OO, and AO approaches.

Method

An quantitative and qualitative analysis of PLA stability which involved four different implementations of a PLA: (i) an OO implementation, (ii) an AO implementation, (iii) a component-based implementation, and (iv) a hybrid implementation where both components and aspects are employed. Each implementation has eight releases and they are functionally equivalent. We used conventional metrics suites for change impact and modularity to measure the architecture stability evaluation of the 4 implementations.

Results

The combination of aspects and components promotes superior PLA resilience than the other PLAs in most of the circumstances.

Conclusion

It is concluded that the combination of aspects and components supports the design of high cohesive and loosely coupled PLAs. It also contributes to improve modularity by untangling feature implementation.     

欠驱动船舶航迹Backstepping自适应模糊控制

针对欠驱动船舶直线航迹跟踪问题,提出一种Backstepping自适应模糊控制方法．在模糊逼近误差存在未知上确界的假设条件下,基于Lyapunov~论证明了闭环系统在所有信号一致最终有界意义下具有均方意义稳定性．本文提出的控制器具有设计直观和结构简洁的特点,并且对参数摄动和外界干扰都具有良好的鲁棒性．在状态变量和控制输入共同约束下的仿真实验验证了该方法的有效性．     

时延加权融合技术的无线传感器网络控制

本文研究了无线传感器网络控制系统的建模、稳定性与控制器设计问题.首先建立一个新的无线传感器网络控制系统模型,然后提出一种用于多个传感器数据融合的时延相关加权均值方法,并通过系统建模及分析,把无线传感器网络控制系统稳定性问题转换成为具有多个传输时延和丢包现象的多传感器单控制器网络控制系统稳定性问题.并利用线性跳变系统理论...     

一类基于观测器的非线性网络化控制系统的绝对稳定性

主要考虑了基于观测器的Lurie网络化控制系统的绝对稳定性问题. 由于采用了基于观测器的反馈控制器, 传感器到控制器的网络诱导时延和控制器到执行器的网络诱导时延不再能合并到一起处理. 首先通过状态增广方法将Lurie网络化控制系统建模为一个多时滞的Lurie系统, 然后利用Newton-Leibniz公式和添加自由权矩阵的方法给出了时滞依赖的稳定性条件. 在此基础上, 给出三种求解控制器和观测器增益矩阵的方法. 此外, 还分别给出了被控对象存在范数有界不确定性和结构不确定性时系统的鲁棒稳定性条件及鲁棒控制器设计方法, 所有得到的结果都是以线性矩阵不等式的形式给出的. 便于利用线性矩阵不等式工具包进行求解. 最后, 通过两个仿真算例说明了方法的可行性和有效性.     

New delay-dependent exponential stability criteria of BAM neural networks with time delays

In this paper, the global exponential stability is investigated for the bi-directional associative memory networks with time delays. Several new sufficient conditions are presented to ensure global exponential stability of delayed bi-directional associative memory neural networks based on the Lyapunov functional method as well as linear matrix inequality technique. To the best of our knowledge, few reports about such “linearization” approach to exponential stability analysis for delayed neural network models have been presented in literature. The method, called parameterized first-order model transformation, is used to transform neural networks. The obtained conditions show to be less conservative and restrictive than that reported in the literature. Two numerical simulations are also given to illustrate the efficiency of our result.     

First-principles study of ground-state properties and phase stability of vanadium nitrides

Using a series of density functional electronic structure total energy calculations, we have systematically studied the ground-state properties and phase stability of vanadium nitrides. Comparison of enthalpy of formation shows that V ₂N is equally stable (polymorphic) in , and Fe₂C phases within a few meV. Formation enthalpy of the various phases considered for perfect stoichiometric V N_1.0 shows that it has enhanced stability in hexagonal WC and NiAs structures in relation to NaCl-type δ-phase. The TiAs phase of VN has nearly same energy as NaCl structure. Comparison of energetics of -type , for x=0 and 0.3333 and of , for x=0, 0.0625, 0.125 and 0.25 shows that vacancies on the nitrogen sublattice lowers the formation enthalpy in relation to respective stoichiometric phases which is in agreement with experiments, as bulk vanadium nitrides are known to be generally non-stoichiometric. The calculated dilute heat of solution for the interstitial nitrogen is found to be in good agreement with experimental values and shows that nitrogen prefers to occupy the octahedral sites in bcc vanadium. The α^′-FeN and martensite structures, considered for the metastable phases of vanadium nitrides, have higher formation enthalpy in relation to equilibrium phases. Analysis of electronic density of states of V ₂N shows that the low energy , and Fe₂C phases are characterized by broad V 3d-N 2p and V 3d bonding bands. Density of states of VN shows that in the low energy WC and NiAs phases some of the antibonding states are made empty, leading to a minimum near the Fermi level. For and , density of states shows that vacancies on the nitrogen sublattice introduce additional filled states in the 3d band below Fermi level enabling enhanced bonding. Comparison between bulk moduli and atomic volumes for the various phases of vanadium nitrides shows that higher bulk moduli are dominated by increased V–N bonds combined with low atomic volumes.     

Sliding mode control for polytopic differential inclusion systems

The stabilization problem of polytopic differential inclusion (PDI) systems is investigated by using sliding mode control. Sliding surface is designed and sufficient conditions for asymptotic stability of sliding mode dynamics are derived. A novel feedback law is established to make the state of system reach the sliding surface in a finite time. Finally, an example is given to illustrate the validity of the proposed design.     

A note on the stability of fractional order systems

In this paper, a new approach is suggested to investigate stability in a family of fractional order linear time invariant systems with order between 1 and 2. The proposed method relies on finding a linear ordinary system that possesses the same stability property as the fractional order system. In this way, instead of performing the stability analysis on the fractional order systems, the analysis is converted into the domain of ordinary systems which is well established and well understood. As a useful consequence, we have extended two general tests for robust stability check of ordinary systems to fractional order systems.