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Time-Varying Momentum-Like Neurodynamic Optimization Approaches With Fixed-Time Convergence for Nash Equilibrium Seeking in Noncooperative Games

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年第6期55卷 3856-3865页

作者： Ju, Xingxing Yang, Xinsong Li, Chuandong Sichuan Univ Coll Elect & Informat Engn Chengdu 610065 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

In this article, several novel time-varying momentum-like neurodynamic optimization approaches are proposed for Nash equilibrium (NE) seeking of noncooperative games. It is shown that the dynamics trajectories converge to NE within fixed-time from arbitrary initial conditions, achieving a quicker convergence rate through the selection of distinct time-varying coefficients. Moreover, the upper bounds of the settling time for the proposed NE seeking neurodynamic approaches are explicitly provided. In addition, the study investigates the robustness of the designed neurodynamic approaches in the presence of bounded noises. The superior convergence properties and practicability of our approaches are demonstrated through a simulation example involving energy consumption games.

关键词： Convergence Games Neurodynamics Optimization Vectors Nash equilibrium Upper bound Time-varying systems laboratories information processing Fixed-time (FT) convergence Nash equilibrium (NE) neurodynamic optimization approaches noncooperative games

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Data-Driven Fault-Tolerant Reinforcement Learning Containment Control for nonlinear Multiagent Systems

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2024年第1期8卷 416-426页

作者： Wang, Xin Zhao, Chen Huang, Tingwen Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400075 Peoples R China TM Univ Qatar Doha 23874 Qatar

This article concentrates on the data-driven containment problem for a class of nonlinear discrete-time multiagent systems via reinforcement learning. A novel two-layer control architecture is designed. In the first layer, a reference model is introduced with which all signals of the multiagent systems will reach synchronization. On account of the critic-actor neural network architecture, an adaptive neural network controller with a multigradient recursive reinforcement learning algorithm and less learning parameters method is designed to tackle the tracking issues and actuator faults. Then in the distributed control layer, the virtual containment control input is developed via policy iteration with critic-actor neural networks such that the containment error will converge to a small neighborhood of the origin. Note that the proposed method makes the solution of optimal containment control problem independent of system dynamics and takes energy costs into consideration. Besides, the semiglobally uniformly ultimately bounded property of signals in the closed-loop system and the policy iteration convergence are guaranteed. Finally, some numerical illustrations are attached to consolidate the effectiveness of our proposed mechanism.

关键词： Mutiagent systems containment control reinforcement learning data-driven actuator faults

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Low complexity fault-tolerant formation control for autonomous underwater vehicles with global prescribed-time performance

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JOURNAL OF THE FRANKLIN INSTITUTE 2025年第1期362卷

作者： Liu, Yiwei Wang, Xin Pang, Ning Tan, Lihua Southwest Univ Coll Westa Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Chongqing Jiaotong Univ Sch Math & Stat Chongqing 400074 Peoples R China

This paper investigates a novel control scheme for multiple autonomous underwater vehicle (AUV) systems in the presence of measurement errors, unknown external disturbances, and actuator faults. The proposed strategy achieves robust formation control while ensuring global prescribed-time performance. By employing passive strategies and event-triggering mechanism, the communication burden between controller and actuator and computational complexity are significantly reduced. All closed-loop signals are proven to be bounded, and Zeno behavior is avoided. The effectiveness of this control scheme is validated through a simulation.

关键词： Autonomous underwater vehicle Global prescribed-time performance Fault-tolerant Low complexity Event-triggering mechanism

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Arbitrary-Time Stable Gradient Flows Using Neurodynamic System for Continuous-Time Optimization

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IEEE TRANSACTIONS ON circuits AND SYSTEMS II-EXPRESS BRIEFS 2023年第12期70卷 4559-4563页

作者： Wen, Hongsong He, Xing Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

In this brief, two arbitrary-time stable gradient flows are proposed to solve the continuous-time optimization problems based on nonlinear neurodynamic system. In contrast to the conventional gradient flow methods, the proposed gradient flows adopt the arbitrary-time sliding mode controller. It is shown that the proposed gradient flows converge to the solution of the optimization problem in arbitrary time under certain mild conditions. Finally, a numerical example is given to verify the main results. In addition, the effectiveness of the proposed gradient flows is further verified by FPGA hardware implementation.

关键词： Arbitrary-time stable sliding mode gradient flow FPGA hardware implementation

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Multi-Leader Bipartite Consensus of Stochastic Delayed Signed Networks With Event-Triggered Unbounded Delayed Impulses

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IEEE TRANSACTIONS ON circuits AND SYSTEMS II-EXPRESS BRIEFS 2023年第3期70卷 1049-1053页

作者： Zhang, Wei Zhou, Zichuan Hong, Nan Southwest Univ Dept Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

Unbounded delayed impulsive controlled multi-leader delayed stochastic signed networks are investigated in this brief. A multileader model based on relays to compensate for topological differences is given. In addition, through an event-triggered mechanism, a probability-based unbounded delayed impulsive control model for bipartite consensus is proposed, which shows that as long as the impulses satisfying certain conditions of time delay are properly blocked, the system is still able to maintain convergence and the Zeno behavior is naturally excluded. Based on the above event-triggered control method, sufficient conditions for the bipartite consensus of multileader and leaderless delayed stochastic signed networks are obtained using the Lyapunov function method and Ito' formula. Finally, the validity of the obtained results is supported by two examples.

关键词： Delays Stochastic processes Delay effects Behavioral sciences Topology Lyapunov methods Couplings Multi-leader stochastic signed networks delayed impulse bipartite consensus

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Event-Triggered Adaptive Neural Control for Full State-Constrained nonlinear Systems with Unknown Disturbances

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COGNITIVE COMPUTATION 2024年第2期16卷 717-726页

作者： Wang, Ziming Wang, Hui Wang, Xin Pang, Ning Shi, Quan Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Hong Kong Univ Sci & Technol Guangzhou Guangzhou 511400 Peoples R China Chongqing Normal Univ Sch Math Sci Chongqing 401331 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

This paper focuses on the adaptive control issue for a class of uncertain nonlinear systems subject to full state constraints and external disturbance. A novel adaptive nonlinear observer is proposed to compensate for disturbance variables in the transformed system. Combining with radial basis function neural networks (RBFNNs) and nonlinear mapping (NM) mechanism, the constrained system is transformed into an unconstrained form and the system uncertainties are effectively handled. Besides that, an adaptive tracking control approach is formulated by invoking backstepping techniques and the event-sampled scheme is utilized to address the sparsity of resources. The adaptive control problem can be addressed with the proposed algorithm, applying the Lyapunov functions, RBF NNs theory, and inequality techniques. Based on the Lyapunov stability theory, it is proved that the system can never violate the specified state constraints and all the closed-loop signals are semiglobally uniformly ultimately bounded (SGUUB). The validity of the proposed approach is well illustrated by a developed numerical example.

关键词： Adaptive backstepping control Disturbance observer Full state constrains First-order differentiator Event-triggered control

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Secure multi-channel information encryption based on integrated optical device

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartC期249卷

作者： Chai, Junxiong Xie, Yiyuan Jiang, Xiao Su, Ye Li, Lili Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China Univ Chongqing Key Lab Networks & Cloud Comp Secur Chongqing 400715 Peoples R China Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

In allusion to the privacy and security problems, a secure multi -channel information protection scheme based on an integrated optical device is proposed in this paper. The information to be encrypted and shared is converted into a QR code. For supporting the multi -channel encryption, a 1- n w encryption algorithm is employed, which possesses the capability to map the original image information into n w seemingly random cipher images. In terms of hardware, an ultra -compact optical encryption device is designed, which consists of two rows of ring resonators coupled to the waveguide. This novel encryption device can output ten cipher images, each transmitted on a separate channel. Meanwhile, the vertical -cavity surface -emitting laser subject to optical injection and optical feedback is researched to generate optical chaos sequences, which are introduced for key generation and QR code encryption. Ultimately, combining the 1- n w encryption algorithm and optical chaos, information protection is implemented based on integrated optics. The simulation results demonstrate the practical feasibility and remarkable effectiveness of the proposed scheme. Furthermore, various security and robustness analyses are performed, and the results reveal that the proposed information protection scheme has a high level of security and robustness. This work is of great significance for the development of optical encryption chips and provides potential applications for secure data sharing.

关键词： information security Optical encryption Plasmonic encryption device Multi-wavelength Optics chaos

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Multifunctional optical logic device based on nanoscale rectangular ring resonator

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JOURNAL OF OPTICS 2024年第2期26卷 025801-025801页

作者： Chai, Junxiong Xie, Yiyuan Tan, Jing Jiang, Xiao Chen, Yan Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Univ Chongqing Key Lab Networks & Cloud Comp Secur Chongqing 400715 Peoples R China

Integrated optical logic devices are essential building blocks for implementing all-optical arithmetic and logic unit. In this paper, an ultra-compact multifunctional optical logic device consisting of a rectangular ring resonator coupled with two parallel metal-insulator-metal waveguides is presented. The transmission characteristics of the structure are analyzed in detail via temporal coupled-mode theory. The finite-difference time-domain simulation results reveal that multiple logic functions can be implemented with the aid of the wavelength division multiplexing technique at different output ports. Specifically, all seven basic types of logic gates, half-adder, half-subtractor, and 2*4 decoder can be implemented by monitoring the transmission of through and drop ports at different wavelengths. More importantly, among these functions, six logic gates (OR, XNOR, NAND, NOR, XOR, and AND) and half-adder functions can be performed simultaneously;the NOT logic operation is performed with controllable output ports and selectable working wavelengths;the half-subtractor and 2*4 decoder functions can be operated simultaneously. The proposed logic device is characterized by a small area overhead, multifunctionality, fast response time, and ultrahigh-speed information processing. It may potentially be applied in on-chip universal and parallel photonic computing units.

关键词： integrated optics logic operation multifunctional device graphene optical computing

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Autonomic Nervous Pattern Recognition of Students' Learning States in Real Classroom Situation

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2023年第1期10卷 220-233页

作者： Chen, Shi Hu, Zhaonian Li, Shanshan Hu, Xiaorou Liu, Guangyuan Wen, Wanhui Southwest China Univ Coll Elec tron & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

The current work applied machine learning methods to analyze students' group and individual learning states in the real classroom environment. The purpose is to provide insights into the learning process for teachers and students, so that they can manage the learning process effectively. We extracted three couples of learning states in real classroom learning, i.e., information input/processing and retrieval/processing states, cognitive load matching and mismatching states, and mental fatigue and nonfatigue states. The recognition of the above three couples of learning states was regarded as five binary classification problems. We collected electrocardiogram (ECG) data from 45 college students during their classes of circuit analysis and calculated the peaks of two consecutive R waves (RR) interval series from the ECG data. For each binary classification problem, RR interval features and classifiers were compared to find the critical feature subsets and suitable classifiers for the recognition of learning states. The generalization accuracies of the machine learning models were in the range of 58.41%-82.35% on the validation sets independent of classifier training and feature selection. The results show that it is feasible to monitor students' learning states through machine learning methods.

关键词： Task analysis Fatigue Electrocardiography Electroencephalography Education Load modeling information processing Artificial intelligence plus education learning states neurophysiological response pattern recognition physiological measurement

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Output Feedback-Based Consensus for nonlinear Multiagent Systems: The Event-Triggered Communication Strategy

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024年第4期35卷 5512-5522页

作者： Tan, Lihua Wang, Xin Li, Chuandong He, Xing Chongqing Jiaotong Univ Sch Math & Stat Chongqing 400074 Peoples R China Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400075 Peoples R China

The current investigation explores the leader-following consensus problem for nonlinear multiagent systems under the output feedback control mechanism and the event-triggered communication mechanism. Owing to the physical instrument constraints, a significant portion of the state variables is not readily available. Therefore, this article put forward a distributed event-based leader-following consensus protocol only using agents' relative output measurements and underlying neighbors. Furthermore, this article develops two event-triggered mechanisms simultaneously, one is the event-triggered communication mechanism in the sensor-to-controller channel, and another is the event-triggered controller update in the controller-to-actuator track. Besides that, it is proven that the developed event-triggered control protocol can settle the leader-following consensus problem of the nonlinear multiagent systems, and the Zeno behavior is excluded in both the channels. Finally, we perform two simulation examples to illustrate the efficacy of the obtained results.

关键词： Multi-agent systems Output feedback Observers Consensus protocol Behavioral sciences Consensus control information processing Event-triggered control leader-following nonlinear multiagent systems output feedback control

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