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Fixed-time stabilization of discontinuous spatiotemporal neural networks with time-varying coefficients via aperiodically switching control

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Science China(Information Sciences) 2023年第5期66卷 182-195页

作者： Xiaofang HU Leimin WANG chuan-ke zhang Xiongbo WAN Yong HE School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which facilitates the handling of time-varying coefficients of SNNs and relaxes the restriction on the non-positive definiteness of the derivative of the Lyapunov function. Besides, a more flexible and economical aperiodically switching control technique is presented to stabilize SNNs within a fixed time,efectively reducing the amount of information transmission and control costs. Under the newly established fixed-time convergence lemma and aperiodically switching controller, many more general algebraic conditions are deduced to ensure the fixed-time stabilization of SNNs. Numerical examples are provided to manifest the validity of the results.

关键词： spatiotemporal neural networks discontinuous activations time-varying coefficients fixed-time stabilization aperiodically switching control

Matrix-injection-based transformation method for discrete-time systems with time-varying delay

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Science China(Information Sciences) 2023年第5期66卷 289-290页

作者： chuan-ke zhang ke-You XIE Yong HE Jinhua SHE Min WU School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

Dear editor,In order to identify the influence of time-varying delays on the stability of control systems represented in a discretetime mode, developing stability criteria of discrete-time delayed systems has received serious attention in the past few decades (see [1–3] and their references).Consider the following linear discrete-time system with a time-varying delay:

关键词： Lyapunov functions

Equivalent input disturbance-based load frequency control for smart grid with air conditioning loads

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Science China(Information Sciences) 2022年第2期65卷 106-123页

作者： Li JIN Yong HE chuan-ke zhang Xing-Chen SHANGGUAN Lin JIANG Min WU School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical Engineering and Electronics University of Liverpool Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Integrating intermittent wind power into power systems results in low or zero inertia, threatening their frequency stability. To accommodate intermittent generations, the demand response(DR) is introduced, and air conditioning loads(ACs) account for an increasing proportion of all loads. The replacement of traditional generators with wind turbines and the ACs user uncertainties produce parameter uncertainties. This paper aims to construct an equivalent input disturbance(EID)-based load frequency control(LFC) strategy for the power system by considering wind power and ACs. First, an open-loop model is constructed for the LFC scheme with parameter uncertainties. Then, the parameter uncertainties and external disturbance are lumped into a fictitious disturbance, which is estimated using an EID *** incorporating the estimation of disturbance into the control input, the disturbance-rejection performance is achieved. Next, the Lyapunov theory is used to derive the two linear-matrix-inequality-based asymptotic stability criteria. A design algorithm is developed for the EID-based LFC scheme by exploiting an overall performance evaluation index. Finally, simulation results for the single-area and two-area LFC schemes show that, compared with the existing approaches, the method presented realizes the better disturbance rejection and higher robustness against parameter uncertainties, wind power fluctuation, and tie-line power ***, its robustness to time delays is verified.

关键词： equivalent input disturbance load frequency control parameter uncertainties wind power air conditioning loads

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Stability analysis of linear systems with two additive time-varying delays via the extended reciprocally convex matrix inequality

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Stability analysis of linear systems with two additive time-...

第40届中国控制会议

作者： Chen Yan chuan-ke zhang Xi-Zi Zhou School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Art and Design Wuhan University of Technology

This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional（LKF） is constructed by introducing a novel augmented term which contains the derivative of state vector into integral terms. Then the extended reciprocally convex matrix inequality together with the Wirtinger integral inequality is used to estimate the derivative of the proposed LKF. As a result, a stability criterion with less conservatism is established. Finally, the advantage of the stability criterion is demonstrated through a numerical example and the application of the stability criterion to stability analysis of load frequency control is illustrated.

关键词： linear system additive time-varying delays stability analysis reciprocally convex matrix inequality

A novel augmented Lyapunov functional for the stability analysis of delayed neural networks

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A novel augmented Lyapunov functional for the stability anal...

第37届中国控制会议

作者： Fei Long Leichao Pang chuan-ke zhang Yong He School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the stability of neural networks with a time-varying *** on the good effectiveness of the augmented Lyapunov-Krasovskii functional（LKF）,some useful integral vectors are summarized and used to construct single integral terms with augmented quadratic integrand so as to develop a novel augmented LKF *** an extended reciprocally convex matrix inequality and an auxiliary function-based inequality are utilized to estimate the derivative of the *** a result,an improved stability criterion is ***,the advantage of proposed method is demonstrated by a numerical example.

关键词： Augmented Lyapunov-Krasovskii functional stability neural networks time-varying delay

Design and implementation of master-slave synchronization for chaotic Lur'e systems using Chua's circuit

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Design and implementation of master-slave synchronization fo...

第43届中国控制会议

作者： Yun-Hao An Hang Xu Yun-Yao zhang Hong-zhang Wang ke-You Xie chuan-ke zhang Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

This paper mainly focuses on designing and implementing master-slave synchronization control of chaotic Lur'e systems using hardware. Firstly, a synchronization criterion for master-slave Lur'e systems is proposed based on LyapunovKrasovskii functional, which fully utilizes the system's information. Then, two inductorless Chua's circuits with state extraction circuits are chosen to construct a novel test-bed platform. Finally, the effectiveness of the synchronization criterion is demonstrated using this test-bed platform.

关键词： Lur'e systems Chaos synchronization Chua's circuit Hardware implementation

Delay-Dependent Stability Analysis of Delayed Discrete-Time Systems via State-Connecting-Based Zero-Value Equations

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Delay-Dependent Stability Analysis of Delayed Discrete-Time ...

第三十九届中国控制会议

作者： ke-You Xie Wen-Hu Chen Li Jin chuan-ke zhang Yong He School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper is concerned with the stability analysis of discrete time-delay system. Firstly, an improved augmented functional form is proposed and the positive definite condition of functional is derived. Then, the forward difference of functional is estimated by applying summation inequalities and a state-connecting-based zero-value equation. As a result, an improved stability criterion is established. Finally, a numerical example is given to show the efficiency and merit of the proposed method.

关键词： Discrete-time systems stability analysis time-varying delay zero-value equation

Stability Analysis of Discrete T-S Fuzzy Systems with Time-Varying Delay Using an Extended Reciprocally Convex Matrix Inequality

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Stability Analysis of Discrete T-S Fuzzy Systems with Time-V...

第37届中国控制会议

作者： Bi-Ying Chen Fei Long chuan-ke zhang Yong He Hui-Qin Xiao School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems College of Electrical and Information Engineering Hunan University of Technology

This paper concerns the stability analysis of discrete Takagi-Sugeno fuzzy systems with time-varying delays.A suitable Lyapunov-Krasovskii functional is constructed,and an extended reciprocally convex matrix inequality is used to estimate the forward difference of the *** a result,a less conservative stability criterion is ***,a numerical example is given to demonstrate the advantage of the proposed method.

关键词： Discrete T-S fuzzy systems time-varying delay stability analysis extended reciprocally convex matrix inequality

基于深度卷积神经网络的运动想象分类及其在脑控外骨骼中的应用

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计算机学报 2017年第6期40卷 1367-1378页

作者：唐智川张克俊李超孙守迁黄琦张三元浙江大学计算机科学与技术学院杭州310027

基于运动想象的脑机接口技术已经广泛的应用于康复外骨骼领域.由于脑电信号的信噪比低,使得脑机接口分类率很难提高.因此,有效的脑电特征提取与分类方法成为现在的研究热点.该文创新地采用基于深度学习理论的卷积神经网络对单次运动想... 详细信息

基于运动想象的脑机接口技术已经广泛的应用于康复外骨骼领域.由于脑电信号的信噪比低,使得脑机接口分类率很难提高.因此,有效的脑电特征提取与分类方法成为现在的研究热点.该文创新地采用基于深度学习理论的卷积神经网络对单次运动想象脑电信号进行特征提取和分类.首先,根据脑电信号时间和空间特征相结合的特性,针对性地设计了一个5层的CNN结构来进行运动想象分类;其次,基于想象左手运动和脚运动设计了运动想象实验范式,获得运动想象实验数据;再次,将该方法应用于公共数据集和实验数据集并建立分类模型,同时与其它3种方法(功率值+SVM、CSP+SVM和MRA+LDA)相比较;最后,将从实验数据集中获得的分类模型(具有最好分类表现)应用于上肢康复外骨骼的实时控制中,验证该文提出方法的可行性.实验结果表明,卷积神经网络方法可以提高分类识别率:卷积神经网络方法应用在公共数据集(90.75%±2.47%)和实验数据集(89.51%±2.95%)中的平均识别率均高于其它3种方法;在上肢康复外骨骼的实时控制中,也验证了CNN方法的可行性:所有被试的平均识别率为88.75%±3.42%.该文提出的方法可实现运动想象的精确识别,为脑机接口技术在康复外骨骼领域的应用提供了理论基础与技术支持.

关键词：深度学习卷积神经网络脑机接口运动想象康复外骨骼人工智能

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