Annular Domain Finite-Time Connective Control for Large-Scale Systems With Expanding Construction

Liu, Yang; Liu, Xiaoping; Jing, Yuanwei; Wang, Huanqing; Li, Xiaohua

doi:10.1109/tsmc.2019.2960009

Cited by 75 publications

(23 citation statements)

References 28 publications

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“…Based on the excellent performance of adaptive control method, over the last decades, it has been widely employed to handle a variety of nonlinear systems, such as single-input and single-output (SISO) nonlinear systems, [1][2][3][4][5] multiple-input and multiple-output (MIMO) nonlinear systems, [6][7][8][9][10] and so on. Among them, MIMO nonlinear systems have attracted considerable attention on account of the complex interactions among sorts of inputs, outputs, and uncertain states.…”

Section: Introductionmentioning

confidence: 99%

Command filtered event‐triggered adaptive control for MIMO stochastic multiple time‐delay systems

Zhu

Liang

Liu

et al. 2021

Intl J Robust & Nonlinear

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In this article, the command filter based adaptive event-triggered control problem for multiple-input and multiple-output multiple time-delay stochastic nonlinear systems is considered. First, a state observer is constructed to estimate the unmeasured states of systems. Then, in the framework of backstepping design, the command filtered and event-triggered techniques are employed to avoid the problem of "explosion of complexity" and save the communication resources, respectively. Meanwhile, by utilizing the command filters, a novel variable separation method is constructed to address the algebraic-loop problem, which caused by the nonstrict-feedback item. The boundedness of the whole signals in systems can be remained, and the given desired trajectories can be followed by the system outputs. Finally, a numerical example is shown to demonstrate the effectiveness of the proposed control method.

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Section: Introductionmentioning

confidence: 99%

Command filtered event‐triggered adaptive control for MIMO stochastic multiple time‐delay systems

Zhu

Liang

Liu

et al. 2021

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

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“…[60][61][62][63][64] In addition, finite-time control can be employed due to the better robustness. 65,66 ACKNOWLEDGEMENT…”

Section: Resultsmentioning

confidence: 99%

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Yang

Xiao

Yin

et al. 2020

Intl J Robust & Nonlinear

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This article investigates the leader-follower consensus problem of a class of non-strict-feedback nonlinear multiagent systems with asymmetric time-varying state constraints (ATVSC) and input saturation, and an adaptive neural control scheme is developed. By introducing the distributed sliding-mode estimator, each follower can obtain the estimation of leader's trajectory and track it directly. Then, with the help of time-varying asymmetric barrier Lyapunov function and radial basis function neural networks, the controller is designed based on backstepping technique. Furthermore, the mean-value theorem and Nussbaum function are utilized to address the problems of input saturation and unknown control direction. Moreover, the number of adaptive laws is equal to that of the followers, which reduces the computational complexity. It is proved that the leader-follower consensus tracking control is achieved without violating the ATVSC, and all closed-loop signals are semiglobally uniformly ultimately bounded. Finally, the simulation results are provided to verify the effectiveness of the control scheme.

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“…In future, the practical finite-time control will be studied for multi-machine system. Besides, the idea of the decentralized control for expanding construction systems in [34] can be considered to study the online expansion of large-scale power systems.…”

Section: Discussionmentioning

confidence: 99%

Semi-Globally Practical Finite-Time ${H}_{\infty}$ Control of TCSC Model of Power Systems Based on Dynamic Surface Control

et al. 2020

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A less-complex semi-globally practical finite-time stability (SGPFS) result is presented for thyristor-controlled series compensation (TCSC) model of the power system by using dynamic surface control (DSC), H ∞ control and prescribed performance control (PPC) in this paper. Meanwhile, a set of preassigned finite-time functions (PFTF) are chosen. The designed controller makes the rotor angle converge to a predefined arbitrary small area within a finite-time interval and other states of the closed-loop system are bounded. In addition, the proposed design method is simpler and the presented result is also easier to be achieved. Finally, simulation results are given to verify the effectiveness and superiority of the theoretical finding. INDEX TERMS Power systems, TCSC, semi-globally practical finite-time control, dynamic surface control, H ∞ theory.

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Annular Domain Finite-Time Connective Control for Large-Scale Systems With Expanding Construction

Cited by 75 publications

References 28 publications

Command filtered event‐triggered adaptive control for MIMO stochastic multiple time‐delay systems

Command filtered event‐triggered adaptive control for MIMO stochastic multiple time‐delay systems

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Semi-Globally Practical Finite-Time ${H}_{\infty}$ Control of TCSC Model of Power Systems Based on Dynamic Surface Control

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