时变耦合复杂网络的有限时间广义外部同步

研究了两个具有时变耦合矩阵的复杂动态网络的有限时间广义外部同步的问题。设计了有限时间控制器, 使两个网络能在有限时间内实现外部同步。利用微分方程的有限时间稳定性理论,得到了复杂网络实现有限时间外部同步的充分条件。为了验证所提方案的有效性,给出了仿真算例,算例验证了有限时间广义外部同步方案的有效性。     

基于积分滑模控制的非理想变时滞 神经网络有限时间同步

研究一类非理想变时滞神经网络的有限时间同步问题.首先,利用驱动-响应概念推导误差系统,并运用同步误差构造一个合适的积分滑模流型,若误差系统的状态轨迹在有限时间内到达滑模面,则同步误差将随其后在有限时间内收敛于零.然后,结合神经元激活函数的约束条件,设计一种合适的滑模控制器,根据所设计的控制器和Lyapunov稳定性理论,误差系统的状态轨迹能够在有限时间内到达滑模面,从而非理想变时滞神经网络的有限时间同步能够实现.最后,通过数值仿真结果验证所提出设计方法的有效性.     

多链接复杂网络指数同步的间歇事件触发控制

本文研究了基于间歇事件触发控制策略的延迟多链接复杂网络的指数同步问题, 设计了一种间歇动态事 件触发控制策略. 相比于间歇静态事件触发控制策略, 本文提出的控制策略是基于控制区间内的动态事件触发, 极 大地减少了事件触发次. 并且, 考虑的间歇控制的控制增益是自适应的, 这具有动态调整的作用. 基于图论和李雅 普诺夫方法, 本文给出了实现延迟多链接复杂网络指数同步的充分条件. 此外, 本文设计的控制策略能够排除Zeno 现象. 并且, 将理论结果应用于一类振子系统的指数同步问题. 最后, 文章给出相应的数值仿真来验证理论结果的有 效性和可行性.     

Cluster,local and complete synchronization in coupled neural networks with mixed delays and nonlinear coupling

In this paper, synchronization analysis is investigated for an array of hybrid coupled neural networks with discrete time-varying delays, distributed time-varying delays and nonlinear coupling. By utilizing a special coupling matrix and Kronecker product, several novel delay-dependent criteria are developed to achieve cluster, local and complete synchronization under a uniform scheme for the coupled neural networks if certain linear matrix inequalities are feasible. The proposed criteria are less conservative than some recently known ones in the literature, which is demonstrated via an example.     

Finite-Time Synchronization of Complex-Valued Neural Networks with Mixed Delays and Uncertain Perturbations

This paper concerns the problem of finite-time synchronization for a class of complex-valued neural networks (CVNNs) with both time-varying and infinite-time distributed delays (mixed delays). Both the driving and response CVNNs are disturbed by external uncertain perturbations, which may be nonidentical. A simple state-feedback controller is designed such that the response CVNNs can be synchronized with the driving system in a settling time. By using inequality techniques and constructing some new Lyapunov–Krasovskii functionals, several sufficient conditions are derived to ensure the synchronization. It is discovered that the settling time cannot be estimated when the interested CVNNs exhibit infinite-time distributed delays, while it can be explicitly estimated for the CVNNs with bounded delays. The settling time is dependent on both the delays and the initial value of the error system. Finally, numerical simulations demonstrate the effectiveness of the theoretical results.     

Finite-time Synchronization of a Class of Coupled Memristor-based Recurrent Neural Networks: Static State Control and Dynamic Control Approach

This paper investigates the problem of the finite-time synchronization of a class of coupled memristor-based recurrent neural networks (MRNNs) with time delays. Based on the drive-response concept and differential inclusions theory, several sufficient assumptions are given to ensure the finite-time synchronization of MRNNs. In order to realize the finite-time synchronization between the drive system and the response system, we design three classes of novel control rules such as static state controller, static output controller, dynamic state controller. Using the theory of differential inclusion, a generalized finite-time convergence theorem and Lyapunov method, the conditions herein are easy to be verified. Moreover, the upper bounds of the settling time of synchronization are estimated and the designed dynamic state controllers have good anti-interference capacity. Finally, two numerical examples are presented to illustrate the effectiveness and the validity of theoretical results.

     

Finite-Time Synchronization of Complex-Valued Neural Networks with Multiple Time-Varying Delays and Infinite Distributed Delays

Neural Processing Letters - This paper investigates finite-time synchronization of complexed-valued neural networks with multiple time-varying delays and infinite distributed delays. By separating...     

Finite-Time Synchronization of Memristive Neural Networks with Proportional Delay

The problem of finite-time synchronization for memristive neural networks (MNNs) with proportional delay is considered. Since proportional delay is unbounded and different from infinite-time distributed delay, the classical finite-time analytical techniques are not applicable anymore. First, a discontinuous state feedback controller is designed such that the delayed MNNs achieve drive-response synchronization in a finite settling time. By using Filippov solution and Lyapunov functional method, sufficient conditions are derived. It is shown that, though the proportional delay is unbounded, complete synchronization can still be realized and the settling time can be explicitly estimated. Second, a special adaptive controller is designed for the finite-time problem in order to reduce the control gains. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.     

Robust Adaptive Synchronization Control for a Class of Perturbed and Delayed Neural Networks

This paper is concerned with the asymptotic synchronization problem of a general neural network using the robust adaptive control technique. It is considered a class of modified Cohen–Grossberg neural networks which is supposed to undergo unknown perturbations caused by state-independent nonlinearities and bounded mixed time-varying delays on neuron amplification and activation functions. An adaptive compensation control strategy is proposed to ensure the elimination of the perturbed and delayed effects by means of adaptive estimations of unknown controller parameters. Through Lyapunov stability theory, it is shown that the proposed adaptive compensation controllers can guarantee the asymptotic synchronization of neural networks without knowing the knowledge of bounds of nonlinearities and delays. A numerical example is provided to illustrate the effectiveness of the developed techniques.     

Finite-time Function Projective Synchronization in Complex Multi-links Networks and Application to Chua’s Circuit

International Journal of Control, Automation and Systems - The article focuses on the problem of finite-time function projective synchronization which is happened in complex multi-links networks...     

变时滞复杂网络同步牵制保性能控制器设计

针对具有可变时滞的复杂网络系统,研究此类系统的同步保性能控制问题。为了使系统同步保性能,设计了一种动态反馈控制器;同时,由于复杂网络的节点较多,考虑到直接控制比较复杂,所以又研究了利用牵制控制使系统达到同步保性能控制的方法。主要运用Lyapunov稳定性理论并结合矩阵不等式处理方法,得出了具有可变时滞性复杂网络系统同步保性能控制器存在的充分条件。所设计的动态反馈控制器在保证系统的渐近稳定条件下使系统的性能指标满足一定的要求。最后给出两个数值仿真说明其有效性。     

Finite-time stability of neutral-type neural networks with random time-varying delays

This paper is devoted to the finite-time stability analysis of neutral-type neural networks with random time-varying delays. The randomly time-varying delays are characterised by Bernoulli stochastic variable. This result can be extended to analysis and design for neutral-type neural networks with random time-varying delays. On the basis of this paper, we constructed suitable Lyapunov–Krasovskii functional together and established a set of sufficient linear matrix inequalities approach to guarantee the finite-time stability of the system concerned. By employing the Jensen's inequality, free-weighting matrix method and Wirtinger's double integral inequality, the proposed conditions are derived and two numerical examples are addressed for the effectiveness of the developed techniques.     

Observer-based distributed coordinated tracking control for multiple simple-pendulum network systems with time-varying delays

For networked control systems consisting of multiple simple-pendulums driven by corresponding DC motors with time-varying communication and input delays, a distributed coordinated controller via observer-based output feedback is designed to solve the tracking problem under both fixed and jointly-connected switching topologies. Firstly, the linearized dynamic model for multiple nonlinear simple-pendulum network systems with DC motors is presented, and the distributed coordinated tracking problem considering time-varying input delays is mathematically described. Then the distributed observer-based tracking control protocol with time-varying communication and input delays is proposed, and simultaneously, both the observer gain and feedback gain are designed. Two examples are simulated to demonstrate consensus tracking for three types of states, i.e., swing angles, angular velocities of multiple simple-pendulums and armature currents of DC motors can be completed utilizing the developed coordinated tracking control with fixed and jointly connected topologies.     

节点维数不同的神经网络系统的有限时间同步

研究了节点维数不同的神经网络系统的有限时间同步问题．假设动态神经网络有限时间同步的驱动系统和响应系统都是分别由不同维数的网络耦合而成的,即各系统中单个网络中节点数量不尽相同．然后给出不同维数的神经网络系统的网络模型,并对非线性反馈控制器进行设计,基于李亚普诺夫稳定性理论得到系统的有限时间同步的充分条件．数值算例证明了所提出的方法的有效性．     

具有执行器故障的四旋翼无人机有限时间容错控制

本文主要研究了四旋翼无人机在外部干扰、执行器存在部分失效和偏置故障并发情况下有限时间轨迹跟踪的控制问题. 通过分析四旋翼无人机动力学特性, 构建了带有外部干扰、执行器机构故障的动力学模型. 基于鲁棒全局快速终端滑模控制算法, 设计了一种有限时间容错控制器, 提高了系统对故障的响应速度. 其次, 针对常值/时变故障和干扰,在控制器设计中采用改进的连续函数进行补偿, 减少了由切换函数引起的系统抖振, 并基于Lyapunov函数对控制器的稳定性进行了分析. 最后, 通过仿真实验验证了所设计控制器的有效性和可靠性, 同时存在执行器故障和外部干扰的情况下, 无人机能够实现较好的轨迹跟踪性能.     

A decoupled designing approach for sampling consensus of multi‐agent systems

This paper introduces the motion‐planning approaches to solve the distributed consensus problems via sampling measurements. First, for first‐order multiagent systems, a class of sampled‐data–based algorithms are developed with arbitrary sampling periods, which solve the asymptotic consensus problem under both directed fixed and random switching topologies. Then, a new kind of distributed consensus algorithms is designed based on sampling measurements for second‐order multiagent systems. Under both the directed fixed and periodical switching topologies, asymptotic consensus problems of second‐order multiagent systems can be solved by using the proposed algorithms. Compared with existing continuous‐time consensus algorithms, one of remarkable advantages of proposed algorithms is that the sampling periods, communication topologies, and control gains are decoupled and can be separately designed, which relaxes many restrictions in controller designs. Finally, some numerical examples are given to illustrate the effectiveness of the analytical results.     

异步时滞切换正系统的有限时间镇定

研究异步切换下时滞切换正系统的有限时间控制问题,即针对控制器切换滞后于子系统切换形成的异步现象,基于平均驻留时间切换方法对切换正系统开展有限时间镇定研究.首先,将每个正子系统运行的区间划分为子系统与控制器匹配和失配区间,并构造多余正Lyapunov-Krasovskii泛函;其次,基于有限时间稳定理论,实现平均驻留时间切换律及异步时滞切换正系统有限时间镇定控制器的联合设计,并给出连续时间和离散时间两种情形下系统有限时间镇定的充分条件;最后,通过两个仿真例子验证所提出方法的有效性.     

Synchronization of Switched Neural Networks with Time‐varying Delays via Sampled‐data Control

This paper investigates sampled‐data synchronization control of switched neural networks with time‐varying delays under average dwell time. Based on the delay system method, the sampled‐data synchronization system is proposed with time‐varying delays and input delays in the unified framework for switched neural networks. By constructing a suitable Lyapunov‐Krasovskii functional and free‐weighting matrix, the relationship between the average dwell time and the maximum sampling interval is revealed to form delay‐dependent exponentially synchronization criteria. The desired mode‐dependent controller under the maximum sampling interval and decay rate is designed. Finally, two numerical examples are provided to demonstrate the effectiveness and feasibility of the proposed techniques.     

Synchronization of complex dynamical networks with switching topology: A switched system point of view

In this paper, we study the synchronization problem for complex dynamical networks with switching topology from a switched system point of view. The synchronization problem is transformed into the stability problem for time-varying switched systems. We address two basic problems: synchronization under arbitrary switching topology, and synchronization via design of switching within a pre-given collection of topologies when synchronization cannot be achieved by using any topology alone in this collection. For the both problems, we first establish synchronization criteria for general connection topology. Then, under the condition of simultaneous triangularization of the connection matrices, a common Lyapunov function (for the first problem) and a single Lyapunov and multiple Lyapunov functions (for the second problem) are systematically constructed respectively by those of several lower-dimensional dynamic systems. In order to achieve synchronization using multiple Lyapunov functions, a stability condition and switching law design method for time-varying switched systems are also presented, which avoid the usual non-increasing condition.     

Global asymptotic stability analysis for neutral-type complex-valued neural networks with random time-varying delays

This paper investigates the global asymptotic stability problem for a class of neutral-type complex-valued neural networks with random time-varying delays. By introducing a stochastic variable with Bernoulli distribution, the information of time-varying delay is assumed to be random time-varying delays. By constructing an appropriate Lyapunov–Krasovskii functional and employing inequality technique, several sufficient conditions are obtained to ensure the global asymptotically stability of equilibrium point for the considered neural networks. The obtained stability criterion is expressed in terms of complex-valued linear matrix inequalities, which can be simply solved by effective YALMIP toolbox in MATLAB. Finally, three numerical examples are given to demonstrate the efficiency of the proposed main results.