统一混沌系统的全局指数吸引集的新结果

研究了参数α∈[1/29,14/173)时,统一混沌系统的全局指数吸引集问题.通过线性变换和广义Lyapunov函数方法,给出了系统最终上界的精确估计.所得结果发展和丰富了现有混沌系统吸引集的结果,并将在混沌控制和同步中得到广泛应用.     

磁盘发电机系统的动力学研究及其在混沌同步中的应用

摘要本文通过构造适当的Lyapunov函数,研究了磁盘发电机系统的最终有界集、正向不变集和全局指数吸引集,得到了该系统界的四维椭球估计表达式.然后将所得到的该系统界的估计应用到完全同步之中去,并做出了相应的数值模拟.     

含约束集值映射超有效解集的连通性

在局部凸拓扑线性空间中给出了含约束集值映射超有效解的连通性定理,当目标函数及约束映射为锥弧连通的集值映射时,其超有效解集是连通的.     

差分包含的有限时间稳定

主要讨论差分包含系统的有限时间稳定问题,基于集值映射和Lyapunov函数给出差分包含的有限时间稳定性的充分条件.     

Liu系统的Lyapunov维数估计

基于Leonov提出的Lyapunov维数理论,通过构造合适的Lyapunov函数,给出了Liu系统不变集的Lyapunov维数估计式.最后并给出了Liu系统混沌吸引子的Lyapunov维数估计.     

广义Lorenz系统的全局指数吸引集及其应用

对于一种广义Lorenz系统,通过线性变换和构造广义Lyapunov函数,给出了全局指数吸引集估计的新方法,并给出了最终界的精确估计式.最后,将结果应用到Chen系统和Lü系统的混沌控制中,给出了保持系统指数稳定的一种线性反馈控制,并且反馈控制律具有更少的保守性.     

基于类Lyapunov函数的非线性切换系统的Reach-While-Stay性质验证

考虑了一类连续时间切换系统在任意切换信号下的Reach-While-Stay性质验证问题,提出了基于类Lyapunov函数的验证方法.首先,利用不变集构建了新的RWS性质判定准则,将RWS性质验证问题转化为关于类Lyapunov函数的非线性约束求解问题,然后运用平方和松弛进行编码,进而将其转化为双线性矩阵不等式问题并应用迭代的半定规划进行求解.最后,通过实例表明了该方法的可行性和有效性.     

考虑时变状态约束与输入饱和的PMSM随机系统指令滤波控制

针对考虑时变状态约束和输入饱和的永磁同步电机随机系统的位置跟踪控制问题,提出了一种基于障碍Lyapunov函数的指令滤波反步控制方案.首先,构造障碍Lyapunov函数以保证电流、转速等状态量不违反时变约束条件.随后,利用模糊逻辑理论处理电机随机系统中的未知非线性项.此外,采用了指令滤波技术与误差补偿机制相结合的方法,不仅解决了传统反步法中出现的“计算爆炸”问题,而且消除了滤波误差的影响.仿真结果表明该控制器能有效抑制输入饱和与随机扰动的影响,提高系统的控制性能,同时能够保证电机系统所有状态在给定的约束范围内.     

基于属性测度的决策系统研究

在属性集和属性测度理论基础上系统地讨论了属性测度综合评价和决策系统.把综合决策系统分为三个子系统;第一个为单指标性能函数分析子系统,第二个为多指标综合性能函数分析子系统;第三个为识别分析子系统.并在属性测度决策系统的基础上,给出了一个应用实例.通过实例的分析,表明该系统是合理、实用和有效的.     

关于集值Pramart的某些结果

本文引进了Boohner可积函数空间L~1[Ω;X]中子集的可分解包的概念,给出了集值随机变量族本性上确界的定义及基本性质。以此为基础,研究了集值Pramart的性质;用类似于实值Snell包的方法给出了集值superpramart的上鞅逼近,证明了集值superpramart在Kuratowski-Mosco意义下的收敛定理。     

Delay-Dependent Criterion for Guaranteed Cost Control of Neutral Delay Systems

In this article, the guaranteed cost control problem for a class of neutral delay systems is investigated. A linear--quadratic cost function is considered as a performance measure for the closed-loop system. Based on the Lyapunov method, delay-dependent criteria, which are expressed in terms of matrix inequalities, are proposed to guarantee the asymptotic stability of the system. The matrix inequalities can be solved easily by various efficient optimization algorithms.     

On Dynamic Output Feedback Guaranteed Cost Control of Uncertain Discrete-Delay Systems: LMI Optimization Approach

In this paper, we consider a design problem of dynamic output feedback controller for guaranteed cost stabilization of discrete-delay systems with norm-bounded time-varying parameter uncertainties. A linear-quadratic cost function is considered as a performance measure for the closed-loop system. Based on the Lyapunov second method, several stability criteria for the existence of the controller are derived in terms of linear matrix inequalities (LMIs). The solutions of the LMIs can be obtained easily using existing efficient convex optimization techniques. A numerical example is given to illustrate the proposed method.     

Dynamic output guaranteed cost controller for neutral systems with input delay

In this paper, we consider a design problem of dynamic output guaranteed cost controller (GCC) of a class of neutral systems with input delay. A quadratic cost function is considered as a performance measure for the closed-loop system. Based on the Lyapunov second method, two stability criteria for existence of the controller are derived in terms of matrix inequalities. The solutions of the matrix inequalities can be easily obtained using existing efficient convex optimization techniques. A numerical example is given to illustrate the proposed design method.     

Multi-objective optimization method for learning thresholds in a decision-theoretic rough set model

For decision-theoretic rough sets, a key issue is determining the thresholds for the probabilistic rough set model by setting appropriate cost functions. However, it is not easy to obtain correct cost functions because of a lack of prior knowledge and few previous studies have addressed the determination of learning thresholds and cost functions from datasets. In the present study, a multi-objective optimization model is proposed for threshold learning. In our model, we integrate an objective function that minimizes the decision cost with another that decreases the size of the boundary region. The ranges of the thresholds and two types of F_measure are used as constraints. In addition, a multi-objective genetic algorithm is employed to obtain the Pareto optimal set. We used 12 UCI datasets to validate the performance of our method, where the experimental results demonstrated the trade-off between the two objectives as well as showing that the thresholds obtained by our method were more intuitive than those obtained using other methods. The classification abilities of the solutions were improved by the F_measure constraints.     

Using adaptive multi-accurate function evaluations in a surrogate-assisted method for computer experiments

In many computer experiments, surrogates are used to assist in searching for certain target points. If the surrogates are defined by response function values evaluated by costly iterative processes, the computational burdens may impede the efficiency of regular surrogate-assisted methods. Instead of computing the fully convergent response function values, we propose to control the function evaluation iterations dynamically to save time on function evaluations without degrading the overall performance. Our new algorithms adaptively determine whether each of the function evaluation iterations should be paused, kept running, or restarted; we then use the approximate function values with various levels of accuracy to construct the surrogates. The numerical results show that the proposed algorithms achieve significant savings when solving super-level set searching problems that involve identifying positive Lyapunov exponents of a dynamical system.     

基于参数依赖Lyapunov泛函不确定时滞系统的H_∞性能分析

研究了具有凸多面体不确定性时滞系统的H∞性能分析问题.基于参数依赖的Lyapunov泛函,导出了系统具有给定H∞性能指标的充分条件.进而,将系统最优H∞性能指标的求取问题转化为一个具有线性矩阵不等式约束的凸优化问题,后者可以应用现有的凸优化方法方进行有效的求解.所提出的方法具有更小的保守性.最后,给出的数值例子说明了提出结果的有效性.     

Model predictive control for switched systems with a novel mixed time/event-triggering mechanism

This paper investigates observer-based model predictive control (MPC) for switched systems with a mixed time/event-triggering mechanism. The problem of predictive control that can achieve receding horizon optimization is considered and solved by minimizing an upper bound of the quadratic cost function. Since the system state may not be fully measured in practice, state observers are employed to estimate. A mixed mechanism including adaptive event-triggering and time-triggering is proposed, which can be switched determined by a threshold describing system performance to better balance system resource utilization and performance requirements. Then, a closed-loop switched system subject to networked-time-delay is modeled. Piecewise Lyapunov function technique and average dwell time approach are utilized to ensure asymptotical stability. Afterwards, MPC controller construction problem is turned into a LMIs feasibility problem. A new solving method of sufficient conditions for co-design of the state observers, feedback controllers and mixed triggering mechanism is derived. Lastly, simulation examples illustrate the correctness and advantages of research content.     

A piecewise ellipsoidal reachable set estimation method for continuous bimodal piecewise affine systems

In this work, the issue of estimation of reachable sets in continuous bimodal piecewise affine systems is studied. A new method is proposed, in the framework of ellipsoidal bounding, using piecewise quadratic Lyapunov functions. Although bimodal piecewise affine systems can be seen as a special class of affine hybrid systems, reachability methods developed for affine hybrid systems might be inappropriately complex for bimodal dynamics. This work goes in the direction of exploiting the dynamical structure of the system to propose a simpler approach. More specifically, because of the piecewise nature of the Lyapunov function, we first derive conditions to ensure that a given quadratic function is positive on half spaces. Then, we exploit the property of bimodal piecewise quadratic functions being continuous on a given hyperplane. Finally, linear matrix characterizations of the estimate of the reachable set are derived.     

Dynamics of two classes of Lorenz‐type chaotic systems

In this article, the dynamical behaviors of two classes of chaotic systems are considered based on generalized Lyapunov function theorem with integral inequalities. Explicit estimations of the ultimate bounds are derived. The results presented in this article contain the existing results as special cases. Computer simulation results show that the proposed method is effective. © 2014 Wiley Periodicals, Inc. Complexity 21: 363–369, 2015     

New estimate the bounds for the generalized Lorenz system

The bound of a chaotic system is important for chaos control, chaos synchronization, and other applications. In the present paper, the bounds of the generalized Lorenz system are studied, based on the Lyapunov function theory and the Lagrange multiplier method. We obtain a precise bound for the generalized Lorenz system. The rate of the trajectories is also obtained. Furthermore, we perform the numerical simulations. Numerical simulations are presented to show the effectiveness of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.