Stochastic Optimal Design for Unknown Linear Discrete‐Time System Zero‐Sum Games in Input‐Output form Under Communication Constraints

In this paper, stochastic optimal strategy for unknown linear discrete‐time system quadratic zero‐sum games in input‐output form with communication imperfections such as network‐induced delays and packet losses, otherwise referred to as networked control system (NCS) zero‐sum games, relating to the H_∞ optimal control problem is solved in a forward‐in‐time manner. First, the linear discrete‐time zero sum state space representation is transformed into a linear NCS in the state space form after incorporating random delays and packet losses and then into the input‐output form. Subsequently, the stochastic optimal approach, referred to as adaptive dynamic programming (ADP), is introduced which estimates the cost or value function to solve the infinite horizon optimal regulation of unknown linear NCS quadratic zero‐sum games in the presence of communication imperfections. The optimal control and worst case disturbance inputs are derived based on the estimated value function in the absence of state measurements. An update law for tuning the unknown parameters of the value function estimator is derived and Lyapunov theory is used to show that all signals are asymptotically stable (AS) and that the estimated control and disturbance signals converge to optimal control and worst case disturbances, respectively. Simulation results are included to verify the theoretical claims.     

一种改进型离散Hopfield学习算法

针对离散Hopfield 神经网络(DHNN) 的权值设计问题, 提出一种改进型学习算法, 并在DHNN动力学分析的基础上设计该学习算法. 利用矩阵分解的方法(MD) 得到正交矩阵, 并采用得到的正交矩阵直接计算DHNN的权值矩阵. 通过该学习算法得到的权值矩阵, 可以很好地存储训练样本的信息, 使测试样本收敛到稳定点. 该学习算法不需要进行分块计算, 减少了计算步骤和计算量, 降低了网络的迭代次数, 从而提高了网络运行速度. 最后, 将该学习算法应用于水质评价, 验证了其有效性和可行性.     

基于奇偶树型交互学习机与遗传算法的密文优化系统

为使图像加密系统具备优化功能,并解决当前遗传算法无法实现全局最优、收敛速率慢等问题,提出奇偶树型交互学习机耦合全局离散遗传算法的密文优化系统。定义权值更新机制,耦合混沌映射,构造奇偶树型交互学习机及其互扰模型。将切断型轮盘赌择取机制引入均匀交叉算子中,以图像分块的相邻像素相关系数和密文信息熵为目标,根据权重理论设计加权适应度函数,提出一种全局离散遗传算法,最终形成"初始加密-密文优化"的加密结构。实验结果表明,与超混沌算法、离散遗传算法、元胞自动机相比,该系统的加密质量较好,并且具备全局优化功能,可优化所有迭代结果,使最终输出密文的信息熵最大,相关系数最小。     

基于EFPN的模糊离散事件系统可诊断性分析

针对模糊有限自动机及模糊Petri网在模糊离散事件系统(Fuzzy Discrete Event System,FDES)行为建模中的不足,提出一种扩展模糊Petri网(Extended Fuzzy Petri Net,EFPN),并基于EFPN构造了FDES行为模型及系统故障诊断器。EFPN以一种新的事件模型为基础对FDES的系统行为进行建模,并根据事件触发矩阵计算下一系统状态中各分量的可能性分布。与模糊有限自动机及模糊Petri网的对比分析表明,在描述FDES模糊事件时,对于同步距离为0的一组事件所造成的影响,EFPN的表达能力强于经典模糊Petri网;在对含有多个状态分量的FDES建模时,EFPN模型的规模远小于模糊有限自动机。在基于EFPN构造的系统行为模型中,运用可达状态标识图分析系统状态集,可有效地构造FDES的故障诊断器,并可据此进行系统可诊断性分析。     

小型轴流压气机清洗两相流场的数值模拟

针对某小型航空发动机单级轴流压气机的清洗需求,以数值模拟结合实验的方法对压气机清洗流场的各种参数进行了分析研究.在初步确定清洗方案的基础上,建立了基于S-A湍流模型的离散相数值模拟理论模型,以经验公式估算喷嘴形成的初始液滴分布,并对喷嘴的实验参数进行了校准,最后以CFD软件进行了流场的数值模拟,计算结果表明：清洗液滴不会对压气机的流场产生明显影响,平面扇形喷嘴在该小型压气机上能获得较好的清洗效果.     

基于DMWT和QIMM 的图像水印算法

利用多尺度分析的思想,对原始图像进行重复行信号预滤波,把标量小波变换扩展到多小波变换后选取变换出来的低频子带进行水印嵌入。为了保证水印信息的安全性,对水印进行加密置乱处理。然后结合量化索引模数调制（QIMM）的优越性能,根据水印的信息不同选择不同的子块进行嵌入并实现了水印的盲提取。实验证明,算法具有良好的视觉性和鲁棒性,并大大扩展了水印的容量。     

基于STL文件的Laplacian网格优化算法

针对直接重构得到且以STL文件格式存储的网格模型质量不高的问题, 提出了一种基于Laplacian坐标的网格模型全局优化算法。该算法在提高三角面片质量的同时可以很好地保持原网格模型的局部几何特征, 其核心思想是通过在最小二乘意义下求解由权重控制的包含顶点位置和拉普拉斯坐标双重约束的线性系统来对网格顶点进行重新定位。从实验结果可以看出, 该算法较以往的Lapacian优化算法在对网格细节特征的保持上有一定优势。     

Stationary policies for lower bounds on the minimum average cost of discrete‐time nonlinear control systems

The paper deals with the control problem of discrete‐time nonlinear systems. The main contribution of this note is to present conditions that assure the existence of stationary policies that generate lower bounds for the minimal long‐run average cost. These lower bounds coincide with the optimal solution when a mild convergence assumption holds. To illustrate the results, the paper presents an application for the simultaneous state‐feedback control problem, and the derived strategy is used to design a real‐time simultaneous control for two direct current motor devices. The dynamics of these two devices are written in terms of a nonlinear algebraic matrix recurrence, which in turn represents a particular case for our general nonlinear approach. The optimal gain for the corresponding simultaneous state‐feedback problem is obtained, and such a gain was implemented in a laboratory testbed to control simultaneously the two direct current motors. Copyright © 2013 John Wiley & Sons, Ltd.     

Robust consensus for uncertain multi‐agent systems with discrete‐time dynamics

This paper investigates robust consensus for multi‐agent systems with discrete‐time dynamics affected by uncertainty. In particular, the paper considers multi‐agent systems with single and double integrators, where the weighted adjacency matrix is a polynomial function of uncertain parameters constrained into a semialgebraic set. Firstly, necessary and sufficient conditions are provided for robust consensus based on the existence of a Lyapunov function polynomially dependent on the uncertainty. In particular, an upper bound on the degree required for achieving necessity is provided. Secondly, a necessary and sufficient condition is provided for robust consensus with single integrator and nonnegative weighted adjacency matrices based on the zeros of a polynomial. Lastly, it is shown how these conditions can be investigated through convex programming by exploiting linear matrix inequalities and sums of squares of polynomials. Some numerical examples illustrate the proposed results. Copyright © 2013 John Wiley & Sons, Ltd.     

A new result on the delay‐dependent stability of discrete systems with time‐varying delays

This paper proposes an improvement to the delay‐dependent stability of discrete systems with time‐varying delays. The approach is based on the observation that the positive definiteness of a chosen Lyapunov–Krasovskii functional does not necessarily require all the involved symmetric matrices to be positive definite, which has been overlooked in the literature. The derived delay‐dependent stability conditions are in terms of linear matrix inequalities. It is theoretically proved that our results are less conservative than the corresponding ones obtained by requiring the positive definiteness of all the symmetric matrices in a chosen Lyapunov–Krasovskii functional. The importance of the present approach is that a great number of delay‐dependent analysis and synthesis results obtained by the aforementioned requirement in the literature can be improved by the present approach without introducing any new decision variables. Copyright © 2013 John Wiley & Sons, Ltd.