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  1. Article ; Online: Finite-time stability of fractional-order nonlinear systems.

    Feng, Zaiyong / Xiang, Zhengrong

    Chaos (Woodbury, N.Y.)

    2024  Volume 34, Issue 2

    Abstract: The paper studies the finite-time stability (FTS) of equilibrium points (EPs) in fractional-order nonlinear systems (FONSs). Classifying the EPs into initial EP and finite-time EP innovatively, equations of the EPs in FONSs are investigated ... ...

    Abstract The paper studies the finite-time stability (FTS) of equilibrium points (EPs) in fractional-order nonlinear systems (FONSs). Classifying the EPs into initial EP and finite-time EP innovatively, equations of the EPs in FONSs are investigated comprehensively, and a unified definition depicting the EPs in the FONSs is proposed. Furthermore, sufficient conditions of the FTS of EPs in FONSs are given. The proposed results are verified with an illustrative example. Thus, different from existing works that declare non-existence of finite-time stable equilibria in FONSs, the existence of finite-time stable EPs in FONSs is confirmed in this paper.
    Language English
    Publishing date 2024-02-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1472677-4
    ISSN 1089-7682 ; 1054-1500
    ISSN (online) 1089-7682
    ISSN 1054-1500
    DOI 10.1063/5.0170419
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Event-Triggered Adaptive Neural Network Sensor Failure Compensation for Switched Interconnected Nonlinear Systems With Unknown Control Coefficients.

    Zhang, Jing / Xiang, Zhengrong

    IEEE transactions on neural networks and learning systems

    2022  Volume 33, Issue 10, Page(s) 5241–5252

    Abstract: In this article, a decentralized adaptive neural network (NN) event-triggered sensor failure compensation control issue is investigated for nonlinear switched large-scale systems. Due to the presence of unknown control coefficients, output interactions, ... ...

    Abstract In this article, a decentralized adaptive neural network (NN) event-triggered sensor failure compensation control issue is investigated for nonlinear switched large-scale systems. Due to the presence of unknown control coefficients, output interactions, sensor faults, and arbitrary switchings, previous works cannot solve the investigated issue. First, to estimate unmeasured states, a novel observer is designed. Then, NNs are utilized for identifying both interconnected terms and unstructured uncertainties. A novel fault compensation mechanism is proposed to circumvent the obstacle caused by sensor faults, and a Nussbaum-type function is introduced to tackle unknown control coefficients. A novel switching threshold strategy is developed to balance communication constraints and system performance. Based on the common Lyapunov function (CLF) method, an event-triggered decentralized control scheme is proposed to guarantee that all closed-loop signals are bounded even if sensors undergo failures. It is shown that the Zeno behavior is avoided. Finally, simulation results are presented to show the validity of the proposed strategy.
    Language English
    Publishing date 2022-10-05
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2021.3069817
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Finite-Time Adaptive Neural Control for a Class of Nonlinear Systems With Asymmetric Time-Varying Full-State Constraints.

    Zhang, Yan / Guo, Jian / Xiang, Zhengrong

    IEEE transactions on neural networks and learning systems

    2023  Volume 34, Issue 12, Page(s) 10154–10163

    Abstract: In this article, an adaptive finite-time tracking control scheme is developed for a category of uncertain nonlinear systems with asymmetric time-varying full-state constraints and actuator failures. First, in the control design process, the original ... ...

    Abstract In this article, an adaptive finite-time tracking control scheme is developed for a category of uncertain nonlinear systems with asymmetric time-varying full-state constraints and actuator failures. First, in the control design process, the original constrained nonlinear system is transformed into an equivalent "unconstrained" one by using the uniform barrier function (UBF). Then, by introducing a new coordinate transformation and incorporating it into each recursive step of adaptive finite-time control design based on the backstepping technique, more general state constraints can be handled. In addition, since the nonlinear function in the system is unknown, neural network is employed to approximate it. Considering singularity, the virtual control signal is designed as a piecewise function to guarantee the performance of the system within a finite time. The developed finite-time control method ensures that all signals in the closed-loop system are bounded, and the output tracking error converges to a small neighborhood of the origin. At last, the simulation example illustrates the feasibility and superiority of the presented control method.
    Language English
    Publishing date 2023-11-30
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2022.3164948
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Neural Adaptive Distributed Formation Control of Nonlinear Multi-UAVs With Unmodeled Dynamics.

    Yu, Yajing / Guo, Jian / Ahn, Choon Ki / Xiang, Zhengrong

    IEEE transactions on neural networks and learning systems

    2023  Volume 34, Issue 11, Page(s) 9555–9561

    Abstract: The problem of neural adaptive distributed formation control is investigated for quadrotor multiple unmanned aerial vehicles (UAVs) subject to unmodeled dynamics and disturbance. The quadrotor UAV system is divided into two parts: the position subsystem ... ...

    Abstract The problem of neural adaptive distributed formation control is investigated for quadrotor multiple unmanned aerial vehicles (UAVs) subject to unmodeled dynamics and disturbance. The quadrotor UAV system is divided into two parts: the position subsystem and the attitude subsystem. A virtual position controller based on backstepping is designed to address the coupling constraints and generate two command signals for the attitude subsystem. By establishing the communication mechanism between the UAVs and the virtual leader, a distributed formation scheme, which uses the UAVs' local information and makes each UAV update its position and velocity according to the information of neighboring UAVs, is proposed to form the required formation flight. By designing a neural adaptive sliding mode controller (SMC) for multi-UAVs, the compound uncertainties (including nonlinearities, unmodeled dynamics, and external disturbances) are compensated for to guarantee good tracking performance. The Lyapunov theory is used to prove that the tracking error of each UAV converges to an adjustable neighborhood of zero. Finally, the simulation results demonstrate the effectiveness of the proposed scheme.
    Language English
    Publishing date 2023-10-27
    Publishing country United States
    Document type Journal Article
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2022.3157079
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Synchronization of Switched Neural Networks via Attacked Mode-Dependent Event-Triggered Control and Its Application in Image Encryption.

    Wang, Hao / Yang, Xinsong / Xiang, Zhengrong / Tang, Rongqiang / Ning, Qian

    IEEE transactions on cybernetics

    2023  Volume 53, Issue 9, Page(s) 5994–6003

    Abstract: It is challenging to synchronize switched time-delay systems when some modes are uncontrolled and the dwell time (DT) of controlled mode is very small. Therefore, in this article, global exponential synchronization almost surely (GES a.s.) in a cluster ... ...

    Abstract It is challenging to synchronize switched time-delay systems when some modes are uncontrolled and the dwell time (DT) of controlled mode is very small. Therefore, in this article, global exponential synchronization almost surely (GES a.s.) in a cluster of switched neural networks (NNs) with hybrid delays (time-varying delay and infinite-time distributed delay) is investigated, where transition probability (TP)-based random mode-dependent average DT (MDADT) switching is considered. A novel mode-dependent pinning event-triggered controller with nonidentical deception attacks is proposed to save the communication resource and derive less conservative results. The two necessary and restrictive conditions in existing papers that the value of the Lyapunov-Krasovskii functional (LKF) before switching instants should be smaller than that after corresponding instant and the DT of each switching mode is restricted by the sampling intervals of the event trigger are moved. Sufficient conditions in terms of linear matrix inequalities (LMIs) are given to guarantee the GES a.s., even though both synchronizing and nonsynchronizing modes coexist and maybe the minimum DT of synchronizing modes is very small. Numerical examples, including image encryption, are provided to demonstrate the merits of the new technique.
    Language English
    Publishing date 2023-08-17
    Publishing country United States
    Document type Journal Article
    ISSN 2168-2275
    ISSN (online) 2168-2275
    DOI 10.1109/TCYB.2022.3227021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Sampled-Data Consensus Protocols for a Class of Second-Order Switched Nonlinear Multiagent Systems.

    Zou, Wencheng / Guo, Jian / Ahn, Choon Ki / Xiang, Zhengrong

    IEEE transactions on cybernetics

    2023  Volume 53, Issue 6, Page(s) 3726–3737

    Abstract: In this study, the sampled-data consensus problem is investigated for a class of heterogeneous multiagent systems (MASs) in which each agent is described by a second-order switched nonlinear system. Owing to the heterogeneity and the occurrence of ... ...

    Abstract In this study, the sampled-data consensus problem is investigated for a class of heterogeneous multiagent systems (MASs) in which each agent is described by a second-order switched nonlinear system. Owing to the heterogeneity and the occurrence of dynamic switching in the MASs, the sampled-data consensus protocol design problem is challenging. In this study, two periodic sampled-data consensus protocols and an event-triggered consensus protocol are developed. Here, we first propose a new periodic sampled-data consensus protocol that involves the local objective trajectory interaction among agents. The protocol is then improved by applying the finite-time control and sliding-mode control techniques. Notably, the improved protocol can be implemented without the transmission of constructed auxiliary dynamical variables, which is a major feature of the present study. It is shown that complete consensus of the underlying MASs can be achieved by the two proposed protocols with only sampled-data measurements. To further reduce the communication load, we introduce an event-triggered mechanism to obtain a new protocol. Finally, the effectiveness of the given schemes is demonstrated by considering a numerical example.
    Language English
    Publishing date 2023-05-17
    Publishing country United States
    Document type Journal Article
    ISSN 2168-2275
    ISSN (online) 2168-2275
    DOI 10.1109/TCYB.2022.3163157
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Mixed l

    Duan, Zhaoxia / Han, Yuchen / Xiang, Zhengrong / Ghous, Imran

    ISA transactions

    2022  Volume 136, Page(s) 361–373

    Abstract: This study is concerned with the problem of the mixed ... ...

    Abstract This study is concerned with the problem of the mixed l
    Language English
    Publishing date 2022-11-30
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2012746-7
    ISSN 1879-2022 ; 0019-0578
    ISSN (online) 1879-2022
    ISSN 0019-0578
    DOI 10.1016/j.isatra.2022.11.030
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Adaptive Fuzzy Decentralized Dynamic Surface Control for Switched Large-Scale Nonlinear Systems With Full-State Constraints.

    Zhang, Jing / Li, Shi / Ahn, Choon Ki / Xiang, Zhengrong

    IEEE transactions on cybernetics

    2022  Volume 52, Issue 10, Page(s) 10761–10772

    Abstract: In this study, an adaptive fuzzy decentralized dynamic surface control (DSC) problem is investigated for switched large-scale nonlinear systems with deferred asymmetric and time-varying full-state constraints. Due to the existence of additional general ... ...

    Abstract In this study, an adaptive fuzzy decentralized dynamic surface control (DSC) problem is investigated for switched large-scale nonlinear systems with deferred asymmetric and time-varying full-state constraints. Due to the existence of additional general nonlinearities, complicated output interconnections, and full-state constraints, it is difficult to address the above control problem using existing methods. Fuzzy-logic systems are, therefore, utilized to approximate the unknown nonlinear functions, and the DSC technique is adopted to overcome the "curse of dimensionality" problem. A novel fuzzy adaptive decentralized controller design is presented using the proposed convex combination technique. Furthermore, it is proven that under the proposed controller and state-dependent switching law, all states of the closed-loop system are bounded and deferred asymmetric, and the time-varying full-state constraints are strictly obeyed. The simulation results are presented to demonstrate the effectiveness of the proposed method.
    MeSH term(s) Algorithms ; Computer Simulation ; Feedback ; Fuzzy Logic ; Nonlinear Dynamics
    Language English
    Publishing date 2022-09-19
    Publishing country United States
    Document type Journal Article
    ISSN 2168-2275
    ISSN (online) 2168-2275
    DOI 10.1109/TCYB.2021.3069461
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Neural-Network Approximation-Based Adaptive Periodic Event-Triggered Output-Feedback Control of Switched Nonlinear Systems.

    Li, Shi / Ahn, Choon Ki / Guo, Jian / Xiang, Zhengrong

    IEEE transactions on cybernetics

    2021  Volume 51, Issue 8, Page(s) 4011–4020

    Abstract: This study considers an adaptive neural-network (NN) periodic event-triggered control (PETC) problem for switched nonlinear systems (SNSs). In the system, only the system output is available at sampling instants. A novel adaptive law and a state observer ...

    Abstract This study considers an adaptive neural-network (NN) periodic event-triggered control (PETC) problem for switched nonlinear systems (SNSs). In the system, only the system output is available at sampling instants. A novel adaptive law and a state observer are constructed by using only the sampled system output. A new output-feedback adaptive NN PETC strategy is developed to reduce the usage of communication resources; it includes a controller that only uses event-sampling information and an event-triggering mechanism (ETM) that is only intermittently monitored at sampling instants. The proposed adaptive NN PETC strategy does not need restrictions on nonlinear functions reported in some previous studies. It is proven that all states of the closed-loop system (CLS) are semiglobally uniformly ultimately bounded (SGUUB) under arbitrary switchings by choosing an allowable sampling period. Finally, the proposed scheme is applied to a continuous stirred tank reactor (CSTR) system and a numerical example to verify its effectiveness.
    Language English
    Publishing date 2021-08-04
    Publishing country United States
    Document type Journal Article
    ISSN 2168-2275
    ISSN (online) 2168-2275
    DOI 10.1109/TCYB.2020.3022270
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Aggregation Analysis for Competitive Multiagent Systems With Saddle Points via Switching Strategies.

    Zhu, Liying / Xiang, Zhengrong

    IEEE transactions on neural networks and learning systems

    2017  Volume 29, Issue 7, Page(s) 2931–2943

    Abstract: This paper addresses the aggregation issues of competitive multiagent systems (CMASs) consisting of competitive agents with multimodes and saddle points. In such CMASs, due to existing mutual competitions, every agent is equipped with finite multimodes, ... ...

    Abstract This paper addresses the aggregation issues of competitive multiagent systems (CMASs) consisting of competitive agents with multimodes and saddle points. In such CMASs, due to existing mutual competitions, every agent is equipped with finite multimodes, and every mode in any agent is described as a second-order linear time-invariant (LTI) control system. When the origin is the same saddle point of all modes of agents, to investigate aggregation of the CMASs with switching strategies, we first use switched LTI systems with saddle points to formulate such CMASs. Then, two new stability concepts, called initial-state-dependent (ISD) stability and initial-state-independent (ISI) stability, are defined for the CMASs. Based on these new stability concepts, a practical criterion of local/global ISI asymptotic aggregation is proposed for the CMASs. A local/global ISD/ISI asymptotical-stabilizing-control observed as distributed controls of multimodes, stabilizing-switching-paths, and a corresponding algorithm are all designed for local/global aggregation of such CMASs with switching delays. Finally, a numerical example illustrates the effectiveness and practicality of our new results.
    Language English
    Publishing date 2017-06-16
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2162-2388
    ISSN (online) 2162-2388
    DOI 10.1109/TNNLS.2017.2710238
    Database MEDical Literature Analysis and Retrieval System OnLINE

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