Article
Engineering, Electrical & Electronic
Yicheng Jiang, Chunbiao Li, Zuohua Liu, Tengfei Lei, Guanrong Chen
Summary: Memristor can be designed based on the topological structure of a dynamical system, such as the Lorenz system, and shows more opportunities for information processing.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Article
Computer Science, Artificial Intelligence
Yongbin Yu, Xiangxiang Wang, Shouming Zhong, Nijing Yang, Nyima Tashi
Summary: This article investigates the problem of robust exponential stability of fuzzy switched memristive inertial neural networks with time-varying delays on mode-dependent destabilizing impulsive control protocol. The study proposes a method to optimize the stability process and reduce time cost effectively. Through simulation, the effectiveness of the results is illustrated.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Chemistry, Multidisciplinary
Suk Yeop Chun, Young Geun Song, Ji Eun Kim, Jae Uk Kwon, Keunho Soh, Ju Young Kwon, Chong-Yun Kang, Jung Ho Yoon
Summary: Technologies combining gas sensors and neuromorphic computing have great potential, but conventional gas sensors lack necessary functions for neuromorphic olfactory systems. This study proposes a chemi-memristive gas sensor based on oxygen vacancy dynamics, which enhances redox reactions and induces rapid current changes. The sensor achieves fast responses, short recovery times, and hysteresis. The sensor's advantageous functionality allows for the experimental demonstration of device-level olfactory systems and the conversion of gas stimuli into synaptic weights.
ADVANCED MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Yongtian Bi, Qi Xu, Hao Geng, Song Chen, Yi Kang
Summary: In recent years, memristive crossbar-based neuromorphic computing systems have shown potential for neural network acceleration. However, issues such as stuck-at faults and process variations in memristor devices affect the computing accuracy of these systems. In this paper, a unified robust network training framework is proposed that considers the impact of both stuck-at faults and variations. Experimental results demonstrate that this framework improves the computation accuracy of neuromorphic computing systems.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Engineering, Mechanical
Mariya Mamajiwala, Debasish Roy
Summary: The solution of a stochastic optimal control problem is related to the Hamilton-Jacobi-Bellman equation, which can be solved using a nonlinear version of the Feynman-Kac formula. By reformulating the HJB equation to have an appropriate initial condition instead of a terminal condition, computational efficiency is improved and integration errors are avoided. This new approach has a significant computational advantage and is more robust, particularly when dealing with stochastically excited oscillators.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2022)
Article
Engineering, Electrical & Electronic
Valeriy A. Slipko, Yuriy Pershin
Summary: The approach based on the Chapman-Kolmogorov equation is introduced to model heterogeneous stochastic circuits that combine binary or multi-state stochastic memristive devices and continuum reactive components. An illustrative example of a series circuit of a binary memristor and capacitor is considered, and some analytical solutions are found. This work provides a novel analytical/numerical tool for modeling complex stochastic networks with a wide range of potential applications.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Article
Automation & Control Systems
Haiqi Peng, Quanxin Zhu
Summary: The aim of the article is to discuss the stochastic fixed-time (FIXT) stability of impulsive stochastic nonlinear time-varying systems. Several novel stability theorems for determining stochastic FIXT stability are established using the multiple Lyapunov method and stochastic analysis theory. The estimation of stochastic settling time is also provided. Compared with other conclusions, these results have wider applications and relaxed constraints.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Corey Lammie, Jason K. Eshraghian, Wei D. Lu, Mostafa Rahimi Azghadi
Summary: Stochastic Computing (SC) is a computing paradigm that enables low-cost and low-power computation using stochastic bit streams and digital logic. By utilizing the stochasticity during switching of CBRAM devices to efficiently generate stochastic bit streams, significant reduction in the size of MAC units is achieved. The scalable architecture consumes approximately 167 μW and occupies 1.55mm^2 in a 40-nm CMOS process, demonstrating stable and efficient performance for parameter optimization in Deep Learning tasks.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2021)
Article
Automation & Control Systems
Shuangyun Xing, Weixing Zheng, Feiqi Deng, Chunling Chang
Summary: In this article, the $H_{\infty}$ control problem for stochastic singular time-varying delay systems under arbitrarily variable samplings is addressed. A novel time-dependent discontinuous Lyapunov-Krasovskii (L-K) functional is built to take advantage of the factual sampling pattern's available properties. Based on this, conditions ensuring the stochastic admissibility for the studied systems are developed. The sampled-data controller design method is obtained and simulation examples demonstrate the correctness and effectiveness of the proposed results.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Multidisciplinary
Jiaxi Chen, Sanyang Liu, Junmin Li, Jin Xie
Summary: This paper investigates the design of adaptive tracking neural controllers for first- and second-order nonlinear multi-agent periodic time-varying systems. It uses Fourier series expansion and neural networks to describe the nonlinear periodic disturbance dynamics, and develops fully distributed adaptive neural controllers based on adaptive estimation to address periodic time-varying perturbations. The efficiency of the proposed controllers is verified through simulations, with convergence of tracking errors to zero neighborhood in the sense of mean square proven based on stochastic Lyapunov stability theory.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Computer Science, Artificial Intelligence
Xiaofan Li, Tingwen Huang, Jian-An Fang
Summary: This article addresses the event-triggered stabilization problem of a new type of Takagi-Sugeno fuzzy complex-valued memristive neural networks, with the design of a fuzzy event-triggered controller and establishment of easily verified sufficient conditions for network stabilization. The proposed event-triggered scheme ensures a nonzero positive lower bound on inter-event time, avoiding Zeno behavior, and the effectiveness of the results is verified through a numerical example.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Yalin Deng, Huasheng Zhang, Jianwei Xia, Wei Sun
Summary: This article investigates the exponential H-infinity tracking control problem of uncertain switched stochastic systems with mixed time-varying delays. A delay-dependent sufficient conclusion is obtained, ensuring the system stability and H-infinity tracking performance. Corresponding controllers are designed based on the stability analysis.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Hui Zhao, Weidong Li, Zhicheng Li, Yu Ren
Summary: This article investigates the problem of dynamic event-triggered control for Markovian jump linear systems with time-varying delay. The proposed dynamic ETC reduces the transmission frequency and conditions of stochastic stability are proposed using a novel stochastic Lyapunov-Krasovskii functional and scaled stochastic small-gain theorem. By designing dynamic ETC, conservatism for stability results is reduced and transmission efficiency is improved.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Xueyan Zhao, Feiqi Deng
Summary: In this article, the Halanay inequality is generalized into the time-varying version without constant to bound the coefficients. The solution of the underlying inequality is estimated using feasible function pairs. Corollaries and numerical examples are provided to illustrate the results. The comparison principle for functional differential inequalities and equations with arbitrary time-varying delays is studied, and the stability and control of stochastic systems with time-varying coefficients and delays are investigated, with a focus on the time variance.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Xiaotai Wu, Wei Xing Zheng, Yang Tang, Xin Jin
Summary: This article introduces the concept of impulsive density to describe the frequency of impulsively occurring events in a time-varying manner, for a more explicit characterization of the number of impulses. Under the impulsive density, the asymptotical stability is considered for impulsive stochastic time-varying systems, and the exponential stability is also investigated for impulsive stochastic time-varying systems with time-delay, extending some existing results. Two examples are presented to demonstrate the effectiveness of the proposed results, including one example of consensus in impulsive time-varying multiagent systems with time-delay.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Peilin Yu, Feiqi Deng
Summary: This article discusses the almost sure stability of stochastic neutral Cohen-Grossberg neural networks (SNCGNNs) with Levy noise, time-varying delays, and Markovian switching. By utilizing the nonnegative semimartingale convergence theorem (NSCT), the neutral Ito formula, M-matrix method, and selecting appropriate Lyapunov function, several stability criteria for SNCGNNs are derived. Additionally, the upper bounds of the coefficients at any mode are given based on the M-matrix theory. Finally, two examples and numerical simulations validate the correctness of the proposed stability criteria.
ASIAN JOURNAL OF CONTROL
(2023)
Article
Mathematics, Applied
Linna Liu, Feiqi Deng, Boyang Qu, Jianyin Fang
Summary: This paper discusses the general decay stability of the backward Euler-Maruyama method for stochastic integro-differential equations (SIDEs). Sufficient conditions are proposed to obtain the general decay stability, which includes the characteristics of generalized stability.
APPLIED MATHEMATICS LETTERS
(2023)
Article
Automation & Control Systems
Tianliang Zhang, Feiqi Deng, Peng Shi
Summary: This article investigates the problem of nonfragile finite-time stabilization for linear discrete mean-field stochastic systems. The uncertainties in control parameters are assumed to be random variables following the Bernoulli distribution. A new approach called the state-transition matrix method is introduced, and necessary and sufficient conditions are derived to solve the stabilization problem. The Lyapunov theorem based on the state-transition matrix also contributes to the theory of discrete finite-time control. A practical example is provided to validate the effectiveness of the newly proposed control strategy.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Rongling Yu, Ping He, Heng Li, Jiannong Cao, Feiqi Deng
Summary: This article investigates the consensus problem of linear multi-agent systems (MASs) with unknown external disturbances under intermittent communication. Firstly, the distributed extended observer is utilized to observe the relative output information and unknown disturbance. Then, a distributed active disturbance rejection intermittent consensus protocol is proposed using the observer information. Finally, a simulation example is provided to demonstrate the effectiveness of the consensus protocol.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Xiongding Liu, Feiqi Deng, Xueyan Zhao, Wu Wei
Summary: This article studies the problem of second-order formation tracking with multiple leaders using intermittent control scheme in stochastic multi-agent networked systems. By considering switching topology and time-varying transmission delay, a formation tracking control protocol is proposed. The mean square stability conditions for formation tracking with multiple leaders are obtained using algebraic graph theory, stochastic systems theory, Lyapunov theory, and Halanay inequality. The proposed intermittent control strategy and stability analysis method alleviate the computation resources of the controller.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Yuanyuan Sun, Feiqi Deng, Yongjia Huang, Peilin Yu
Summary: This paper addresses the event-triggered stabilization of switching systems with persistent dwell time (PDT) using dynamic input quantization. The co-design of the event-triggered mechanism, zoom variable, and PDT switching condition is achieved to eliminate the effect of asynchrony and quantization errors on stability. The proposed method includes the design of the zoom variable update law based on PDT properties, consideration of asynchrony in stability analysis, and the proposal of a common lower bound for the triggered interval to eliminate Zeno behavior. Numerical simulation verifies the validity of the method.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Yongjia Huang, Feiqi Deng, Fangzhe Wan, Peilin Yu, Yuanyuan Sun
Summary: This paper focuses on the stabilization problem of a class of stochastic nonlinear systems under periodic sampled-data state feedback subject to input saturation. An auxiliary variable is introduced to handle the saturation nonlinearity and characterize the estimate of the region of attraction of the origin. Stability criteria are established in the form of parametric conditions. The relationship between the estimate of the region of attraction and controller gain, sampling period is analyzed, and the effectiveness of the results is demonstrated through an example and an application for synchronization of two Chua's Circuits.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Computer Science, Artificial Intelligence
Xiaobin Gao, Feiqi Deng, Chun-Yi Su, Pengyu Zeng
Summary: This article considers the security control issue of nonlinear networked systems using an interval type-2 fuzzy modeling strategy. A stochastic scheduling strategy called Markovian communication protocol is introduced to coordinate the sensor transmission order in order to avoid communication congestion. An asynchronous observer is designed to estimate the unmeasured states via the hidden Markov model. Additionally, a comprehensive scenario on deception attack is considered, where attacks occur in both the sensor-observer and controller-actuator communication channels with different types of deception signals. Some sufficient conditions for ensuring the ultimately boundedness of the resulting closed-loop system are obtained using the slack matrix approach and stochastic analysis technique. Simulation results demonstrate the validity of the proposed protocol-based fuzzy control method.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Xiongding Liu, Feiqi Deng, Wu Wei, Fangzhe Wan, Peilin Yu
Summary: This article investigates the mean-square exponential stability of stochastic nonlinear delay systems with dynamic event-triggered mechanism under periodically intermittent control scheme. To avoid Zeno behavior, a triggered mechanism with a fixed positive lower bound for the inter-execution time is constructed. An auxiliary system with dynamic event-triggering mechanism under continuous control is introduced, and the sufficient conditions and mean-square exponential stability of the auxiliary system are obtained using Lyapunov theorem and Halanay inequality. The exponential stability of the system under intermittent control is also proved by using the comparison theorem. Moreover, the lower bound of the duty cycle for a fixed period under intermittent controller is derived. The theoretical results are applied to the consensus of stochastic nonlinear delay networked multi-agent systems (MASs) with dynamic event-triggered mechanism, and numerical examples are provided to verify the effectiveness of the proposed methods.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Peilin Yu, Feiqi Deng, Xinzhi Liu, Yuanyuan Sun
Summary: This article investigates the polynomial integral input-to-state stability in mean square (ms-PIISS) and polynomial (t + 1)(?)-weighted integral input-to-state stability in mean square ((t + 1)(?)-weighted ms-PIISS) for pantograph stochastic systems. The above stability is achieved through dynamic event triggered mechanism and static event-triggered mechanism. Our event-triggered mechanisms (ETMs) force a pause time after each successful execution to avoid Zeno behavior and save communication resources. The Hanalay-type inequality is utilized to obtain a less conservative stability criterion and a collaborative design method of ETM and linear controller is proposed. An example is presented to illustrate the effectiveness of the collaborative design process.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Computer Science, Cybernetics
Xiaojing Zhong, Yukun Yang, Feiqi Deng, Guiyun Liu
Summary: This study investigates the intermittent control of a rumor propagation system with anti-rumor mechanism. It examines the interaction with the anti-rumor mechanism, including the existence and stability of two boundary equilibriums, as well as the conditions for bistability behavior. Deterministic and stochastic control strategies with aperiodically intermittent control time are designed to combat rumor spreading. The minimum control intensities, related to the control ratio and system parameters, are obtained.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Lunan Zheng, Weiqi Yu, Zongqing Xu, Zhijun Zhang, Feiqi Deng
Summary: A novel discrete error redefinition neural network (D-ERNN) is proposed in this paper to solve time-varying quadratic programming problems. Compared with traditional neural networks, the proposed network demonstrates superior performance in terms of convergence speed, robustness, and overshoot. The article also analyzes and proves the reliability of the network by discussing parameter selection and step size. Additionally, the discretization of ERNN and its comparison with other related neural networks are presented.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Shixian Luo, Qinghua Zhong, Yan Jiang, Feiqi Deng, Zhipei Hu
Summary: This paper proposes a systematic framework for stability and guaranteed cost control of linear impulsive systems subject to random time- and event-triggering impulses. The proposed event-triggered controller is shown to guarantee at least the same quadratic performance function bound as the designed time-triggered guaranteed cost controller, but with a larger, or at most equal, average inter-transmission time. In addition, a stochastic dynamic event-triggered control strategy is proposed to solve sampled-data control systems in the presence of sporadic measurements or stochastic sampling.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Bo Zhang, Liangyi Cai, Feiqi Deng, Shengli Xie
Summary: This paper introduces the stabilization by aperiodically intermittent sampling stochastic noise as a new method for solving the consensus problem of a class of homogeneous multi-agent systems. It designs a multiplicative noise as a control input to stabilize the error system of the multi-agents. The average noise control rate is used to estimate the working time of the intermittent noise, while a novel piecewise analysis technique is adopted to estimate the mean square of the error state. The sufficient criteria for the stability of the error system are obtained.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Automation & Control Systems
Yuanyuan Sun, Feiqi Deng, Peilin Yu
Summary: This paper investigates the problem of event-triggered control of stochastic nonlinear delayed systems with state quantization. An event-triggered mechanism and state quantization are introduced in the control scheme to reduce the communication burden and computational cost while ensuring the stability of the closed-loop system. Both static and dynamic event-triggered mechanisms are proposed, allowing for the adjustment of parameters and selection of suitable configurations to reduce communication times and enhance resource conservation.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
