Dissipativity of extended Pouzet–Runge–Kutta methods for neutral delay integro-differential equations

This paper is concerned with dissipativity of extended Pouzet–Runge–Kutta methods for neutral delay integro-differential equations. The finite-dimensional and infinite-dimensional dissipativity results of the (k, l)-algebraically stable extended Pouzet–Runge–Kutta methods are obtained under suitable conditions.     

Exponentially incremental dissipativity for nonlinear stochastic switched systems

ABSTRACT

In this paper, we investigate the exponentially incremental dissipativity for nonlinear stochastic switched systems by using the designed state-dependent switching law and multiple Lyapunov functions approach. Specifically, using incremental supply rate as well as a state dissipation inequality in expectation, a stochastic version of exponentially incremental dissipativity is presented. The sufficient conditions for nonlinear stochastic switched systems to be exponentially incrementally dissipative are given by the designed state-dependent switching law. Furthermore, the extended Kalman–Yakubovich–Popov conditions are derived by using two times continuously differentiable storage functions. Moreover, the incremental stability conditions in probability for nonlinear stochastic switched systems are derived based on exponentially incremental dissipativity. The exponentially incremental dissipativity is preserved for the feedback-interconnected nonlinear stochastic switched systems with the composite state-dependent switching law; meanwhile, the incremental stability in probability is preserved under some certain conditions. A numerical example is given to illustrate the validity of our results.     

Global dissipativity of memristor-based complex-valued neural networks with time-varying delays

Memristor is the new model two-terminal nonlinear circuit device in electronic circuit theory. This paper deals with the problem of global dissipativity and global exponential dissipativity for memristor-based complex-valued neural networks (MCVNNs) with time-varying delays. Sufficient global dissipativity conditions are derived from the theory of M-matrix analysis, and the globally attractive set as well as the positive invariant set is established. By constructing Lyapunov–Krasovskii functionals and using a linear matrix inequality technique, some new sufficient conditions on global dissipativity and global exponential dissipativity of MCVNNs are derived. Finally, two numerical examples are presented to demonstrate the effectiveness of our proposed theoretical results.     

Dissipativity and passivity analysis of Markovian jump impulsive neural networks with time delays

This paper discusses the issue of dissipativity and passivity analysis for a class of impulsive neural networks with both Markovian jump parameters and mixed time delays. The jumping parameters are modelled as a continuous-time discrete-state Markov chain. Based on a multiple integral inequality technique, a novel delay-dependent dissipativity criterion is established via a suitable Lyapunov functional involving the multiple integral terms. The proposed dissipativity and passivity conditions for the impulsive neural networks are represented by means of linear matrix inequalities. Finally, three numerical examples are given to show the effectiveness of the proposed criteria.     

图神经网络在复杂图挖掘上的研究进展

图神经网络对非欧式空间数据建立了深度学习框架,相比传统网络表示学习模型,它对图结构能够实施更加深层的信息聚合操作.近年来,图神经网络完成了向复杂图结构的迁移,诞生了一系列基于复杂图的图神经网络模型.然而,现有综述文章缺乏对复杂图神经网络全面、系统的归纳和总结工作.将复杂图分为异质图、动态图和超图3种类型.将异质图神经网络按照信息聚合方式划分为关系类型感知和元路径感知两大类,在此基础上,分别介绍普通异质图和知识图谱.将动态图神经网络按照处理时序信息的方式划分成基于循环神经网络、基于自编码器以及时空图神经网络三大类.将超图神经网络按照是否将超图展开成成对图划分为展开型和非展开型两大类,进一步按照展开方式将展开型划分成星形展开、团式展开和线形展开3种类型.详细阐述了每种算法的核心思想,比较了不同算法间的优缺点,系统列举了各类复杂图神经网络的关键算法、(交叉)应用领域和常用数据集,并对未来可能的研究方向进行了展望.     

离散区间二型Tagaki-Sugeno模型时滞系统广义耗散控制设计

对带有时变时滞和外部扰动的一类离散区间二型Tagaki-Sugeno(T–S)模型非线性系统,研究了其广义耗散性能分析与状态反馈控制器的设计问题.与一型T–S模糊系统相比,区间二型模糊系统能更好地处理隶属函数中的不确定信息.首先,通过模型转换的方法,对系统的滞后状态进行变换,从而将时变时滞的不确定性从原系统中分离出.根据转换后的仅含定常时滞和具有有界误差范数的两个子系统,利用时滞依赖的李雅普诺夫-克拉索夫斯基泛函方法推导出了使系统渐近稳定并具有广义耗散性能的充分条件.接着,设计了保证闭环系统渐近稳定并具有广义耗散性能指标的状态反馈控制器.最后由数值仿真验证了设计方法的有效性.     

Event-triggered Extended Dissipative Control for Networked Singular Systems

In this paper, an event-triggered extended dissipative control problem for networked singular systems is investigated, where the extended dissipativity analysis unifies the H_∞ performance, L₂ − L_∞ performance, passivity, (Q, S, R)-dissipativity in one framework. Under the event-triggered scheme, the closed-loop system is modeled as a time-delay system. Some sufficient conditions for extended dissipativity are developed and presented in terms of linear matrix inequalities (LMIs). Then the design of the state feedback controller becomes a matter of solving a set of LMIs. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

     

Reliable filtering with extended dissipativity for uncertain systems with discrete and distributed delays

This paper deals with the problem of reliable filter with extended dissipativity for uncertain systems with discrete and distributed delays, and sensor-failure model of this system is assumed to be concerned with Markovian behaviour. First, based on a novel Lyapunov–Krasovskii functional, a sufficient condition, which ensures that the filtering error system is stochastically stable and extended dissipative, is obtained. Second, mode-dependent conditions for the solvability to the reliable filter with extended dissipativity problem are given in terms of linear matrix inequalities (LMIs). The desired filter parameters can be derived by using feasible solutions to the presented LMIs. Finally, two numerical examples are given to illustrate the effectiveness of the filter design method.     

Fault detection problem for discrete-time impulsive system using mixed dissipativity approach

This article studies the fault detection problem for a class of discrete-time impulsive systems using mixed dissipativity theory. First, under the impulsive effects, a fault diagnosis observer is designed such that it is insensitive to disturbances, and sensitive to faults. Then, a mixed dissipativity concept is introduced to deal with impulsive effects, disturbances insensitivity condition and faults sensitive condition in one framework such that the impulsive error dynamic is dissipative with respect to the proposed mixed supply rate. Based on the proposed mixed supply rate, sufficient conditions are obtained to guarantee the dissipativity of the impulsive estimation error dynamic. Moreover, sufficient conditions are established for the existence of the desired fault observer. The corresponding solubility conditions for the designs of the desired observer are also obtained. Finally, simulation results are proposed to demonstrate the effectiveness of our proposed strategy.     

Geometrically (Q,S, R)‐Incremental Dissipativity and Incremental Stability for Switched Time‐Varying Nonlinear Discrete‐Time Systems

This paper investigates geometrically (Q,S,R)‐incremental dissipativity and incremental stability for switched time‐varying nonlinear discrete‐time systems. A geometrically (Q,S,R)‐incremental dissipativity concept is proposed for switched nonlinear discrete‐time systems by using multiple storage functions and multiple incremental supply rate. Furthermore, the sufficient conditions of geometrically (Q,S,R)‐incremental dissipativity are given under the design of state‐dependent switching law. The incremental stability conditions are derived for geometrically (Q,S,R)‐incrementally dissipative switched systems. By designing of a composite state‐dependent switching law, the feedback interconnected switched systems are ensured to be geometrically (Q,S,R)‐incrementally dissipative. A numerical example is given to illustrate the validity of the proposed approach.     

Non‐Fragile Extended Dissipativity Control Design for Generalized Neural Networks with Interval Time‐Delay Signals

The problem of non‐fragile extended dissipative control design for a class of generalized neural networks (GNNs) with interval time‐delay signals is investigated in this paper. By constructing a suitable Lyapunov‐Krasovskii functional (LKF) with double and triple integral terms, and estimating their derivative by using the Wirtinger single integral inequality (WSII) and Wirtinger double integral inequality (WDII) technique respectively, and that is mixed with the reciprocally convex combination (RCC) approach. A new delay‐dependent non‐fragile extended dissipative control design for GNNs are expressed in terms of the linear matrix inequalities (LMIs). Then, the desired non‐fragile extended dissipative controller can be obtained by solving the linear matrix inequalities (LMIs). Furthermore, a non‐fragile state feedback controller is designed for GNNs such that the closed‐loop system is extended dissiptive. Thus, the non‐fragile extended dissipative controller can be adopted to deal with the non‐fragile performance, non‐fragile performance, non‐fragile passive performance, non‐fragile mixed and passivity performance, and non‐fragile dissipative performance for GNNs by selecting the weighting matrices. Finally, simulation studies are demonstrated for showing the feasibility of the proposed method. Among them, one example was supported by the real‐life application of the quadruple tank process system.     

Stochastic stability and extended dissipativity analysis for uncertain neutral systems with semi‐Markovian jumping parameters via novel free matrix–based integral inequality

This paper investigates the issues of stochastic stability and extended dissipativity analysis for uncertain neutral systems with semi‐Markovian jumping parameters. A new criterion about the stochastic stability and extended dissipativity of uncertain neutral systems with semi‐Markovian jumping parameters is obtained based on the new Lyapunov‐Krasovskii functionals together with the introduced novel free matrix–based integral inequality. The major contribution of this study is that the stochastic stability and extended dissipativity concept for uncertain neutral systems with semi‐Markovian jumping parameters can be developed to simultaneously analyze the solutions of the L₂ ? L_∞ performance, H_∞ action, passivity behavior, and dissipativity by selecting different weighting matrices. Finally, several interesting numerical examples are provided to show the effectiveness and less conservatism of the proposed method.     

Transverse contraction criteria for existence,stability, and robustness of a limit cycle

This paper derives a differential contraction condition for the existence of an orbitally-stable limit cycle in an autonomous system. This transverse contraction condition can be represented as a pointwise linear matrix inequality (LMI), thus allowing convex optimisation tools such as sum-of-squares programming to be used to search for certificates of the existence of a stable limit cycle. Many desirable properties of contracting dynamics are extended to this context, including the preservation of contraction under a broad class of interconnections. In addition, by introducing the concepts of differential dissipativity and transverse differential dissipativity, contraction and transverse contraction can be established for interconnected systems via LMI conditions on component subsystems.     

Implications of dissipativity,inverse optimal control,and stability margins for nonlinear stochastic feedback regulators

In this paper, we derive stability margins for optimal and inverse optimal stochastic feedback regulators. Specifically, gain, sector, and disk margin guarantees are obtained for nonlinear stochastic dynamical systems controlled by nonlinear optimal and inverse optimal Hamilton‐Jacobi‐Bellman controllers that minimize a nonlinear‐nonquadratic performance criterion with cross‐weighting terms. Furthermore, using the newly developed notion of stochastic dissipativity, we derive a return difference inequality to provide connections between stochastic dissipativity and optimality of nonlinear controllers for stochastic dynamical systems. In particular, using extended Kalman‐Yakubovich‐Popov conditions characterizing stochastic dissipativity, we show that our optimal feedback control law satisfies a return difference inequality predicated on the infinitesimal generator of a controlled Markov diffusion process if and only if the controller is stochastically dissipative with respect to a specific quadratic supply rate.     

Global Dissipativity of Inertial Neural Networks with Proportional Delay via New Generalized Halanay Inequalities

This article is devoted to the global dissipativity of inertial neural networks with proportional delay. A novel generalized Halanay inequality which involves proportional delay is established. By constructing a new generalized Halanay inequality, several new explicit delay-independent conditions are derived in terms of linear matrix inequalities to ensure the global dissipativity of the considered system. Moreover, a new differential delay inequality which involves unbounded time-varying delay is considered. Due to the proportional delay is one type of unbounded time-varying delays, new analysis techniques can effectively avoid the difficulties caused by proportional delay by applying a new differential delay inequality. Especially, several novel delay-dependent sufficient conditions are obtained to guarantee the global dissipativity of the considered system. Finally, two simulations examples are provided to illustrate the validity of the proposed theoretical analysis.     

Robust extended dissipativity criteria for discrete-time uncertain neural networks with time-varying delays

In this draft, we consider the problem of robust extended dissipativity for uncertain discrete-time neural networks (DNNs) with time-varying delays. By constructing appropriate Lyapunov–Krasovskii functional (LKF), sufficient conditions are established to ensure that the considered time-delayed uncertain DNN is extended dissipative. The derived conditions are presented in terms of linear matrix inequalities (LMIs). Numerical examples are provided to illustrate the superiority of this result.

     

Extended dissipative output-feedback control for discrete-time bidirectional associative memory neural networks via delay-partitioning approach

This paper is concerned with the analysis of an extended dissipativity performance for a class of bidirectional associative memory (BAM) neural networks (NNs) having time-varying delays. To achieve this, the idea of the delay-partitioning approach is used, where the range of time-varying delay factors is partitioned into a finite number of equidistant subintervals. A delay-partitioning based Lyapunov–Krasovskii function is introduced on these intervals, and some new delay-dependent extended dissipativity results are established in terms of linear matrix inequalities, which also depend on the partition size of the delay factor. Further, numerical examples are performed to acknowledge the extended dissipativity performance of delayed discrete-time BAM NN; further, four case studies were explored with their simulations to validate the impact of the delay-partitioning approach.     

Extended dissipativity-based non-fragile control for multi-area power systems with actuator fault

This paper addresses the issue of reliable load frequency control design of an uncertain multi-area power system with constant time delays and disturbances via non-fragile sampled-data control approach. In particular, the parameter uncertainties are assumed to be randomly occurring which are described by the Bernoulli distributed sequences. By constructing a suitable Lyapunov–Krasovskii functional together with Wirtinger-based inequality, a new set of sufficient conditions in terms of linear matrix inequalities is obtained to ensure the asymptotic stability and extended dissipativity of the multi-area power system not only when all actuators are operational, but also in case of some actuator failures. Finally, simulation results are conducted to validate the effectiveness of the proposed control design technique.     

时变时滞神经网络的时滞相关鲁棒稳定性和耗散性分析

研究时变时滞神经网络的鲁棒稳定性和耗散性问题.充分利用积分项的时滞信息和激励函数条件构造一个合适的增广LK泛函;利用自由矩阵积分不等式处理LK泛函的导数,得到一个低保守性的时滞相关稳定判据;将所获得的结论延伸至神经网络的耗散性分析,并推导出一个确保神经网络严格$(\mathcalX, \mathcalY,\mathcalZ)-\gamma$-耗散的充分条件.最后通过3个数值算例验证了所提出方法的可行性和优越性.     

On stability and dissipativity of some classes of complex systems

A new form of aggregation of complex systems was proposed and used to determine the conditions for asymptotic stability and uniform dissipativity in nonlinear approximation with the view of establishing criteria for absolute stability and absolute dissipativity. The results obtained were used to analyze dynamics of some the mechanical and biological systems.