Exponential H∞ Filtering for Continuous-Time Switched Neural Networks Under Persistent Dwell-Time Switching Regularity

This paper investigates the finite-time synchronization issue for semi-Markov jump inertial neural networks, in which the sampled-data control is employed to alleviate the burden of the limited communication bandwidth. Due to the existence of inertial item, the semi-Markov jump inertial neural networks as hybrid neural systems, are depicted with secondorder derivatives for the first time, which can be turned to firstorder derivatives by the variable transformation. Furthermore, by applying appropriate integral inequalities and constructing the proper Lyapunov functional, some sufficient conditions, which not only guarantee the finite-time synchronization of the resulting error system but also ensure a specified level of L2-L∞ performance, are acquired based on the optimization of integral inequality technique. A numerical example is, eventually, proposed to substantiate the validity of the developed method.

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“…then, in accordance with (17) , the condition (27) is obtained. Thus, in line with Definition 1, the error system (9) is MSSFTS.…”

Section: A Proof Of Theoremmentioning

confidence: 83%

“…. , 8}) such that conditions (14)- (17) and the following inequalities are satisfied for each m ∈ N, i,…”

Section: B the Sampled-data Controller Designmentioning

confidence: 99%

Finite-Time $\mathcal {L}_{2}$-$\mathcal {L}_{\infty }$ Synchronization for Semi-Markov Jump Inertial Neural Networks Using Sampled Data

Wang

Shen

et al. 2021

IEEE Trans. Netw. Sci. Eng.

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“…Proof: We know that ψ = −(∇H) T R 1 (∇H) ≤ 0 under the action of controller (24) and adaptive law (25). Let Q(x) = (∇H) T R 1 (∇H), the energy storage function V (x) ≥ 0, Q(x) ≥ 0 satisfies dissipative inequality (2) in the presence of (13), and the system has L 2 interference suppression characteristics, so the system (1) is asymptotically stable near the equilibrium point.…”

Section: Design Of Value Controller Based On Hamilton Adaptive Mmentioning

confidence: 99%

“…[20]- [22] considers H ∞ fault detection observer design in the finite frequency domain for a class of linear parameter varying descriptor systems. In paper [23]- [25] study the problem of fault detection and estimation for switched systems. Switching systems are generally composed of a family of subsystems and switching rules that describe the connections between them.…”

Section: Introductionmentioning

confidence: 99%

Valve Controller Design of Multi-Machine Power Systems Based on Adaptive Hamilton Minimax Method

Wang

Dong

et al. 2020

IEEE Access

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This paper describes an application of nonlinear adaptive Hamilton minimax control to multimachine power systems with steam valve controllers. The controllers are designed explicitly to maintain transient stability of systems. First, the feedback link is introduced to transform the traditional power system model into Hamilton structure. It is worth mentioning that in the process of building the system model and designing the controllers, this paper considers the problem of interconnection interference. The proposed controllers enable the system to have L 2 interference suppression characteristics in the case of maximum disturbance. Finally, the simulation results show that the adaptive Hamilton minimax method has better transient performance. INDEX TERMS Hamilton control, multi-machine power system, transient stability, adaptive method.

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“…In the last decade, switched systems have attracted enormous attention due to their wide applications in automatic control system, 1,2 power electronic system, 3 and so on. Considering the significance both in theory and practice, many issues concerning linear or nonlinear switched systems have been reported, including stability and stabilization, [4][5][6][7][8][9][10] H ∞ filtering, 11 and synchronization. 12 It is well known that time-delays are ubiquitous and they will lead to the deterioration of system performance and even cause instability.…”

Section: Introductionmentioning

confidence: 99%

Sampled‐data exponential stabilization of switched nonlinear delayed systems with asynchronous switching

Huang

Wang

et al. 2020

Intl J Robust & Nonlinear

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In this article, the exponential stabilization for a class of switched nonlinear delayed systems is addressed via aperiodic sampled-data control with asynchronous switching. A new type of looped multiple Lyapunov-Krasovskii functionals (LKFs) is developed, which depend both on the system modes and on the controller modes. Moreover, the constructed looped LKFs are discontinuous and relax restrictions on positive definiteness that is only required at the sampling instants and at the switching instants of system modes. Based on the looped multiple LKFs, the average dwell time approach, and some estimation techniques, a less conservative stability criterion is derived to ensure the exponential stability of the closed-loop system. Furthermore, by decoupling the matrix inequalities in the stability criterion, a LMI-based design algorithm for the control gains is developed, which gets further refined and becomes more flexible due to the introduction of the two adjustable parameters. Two simulation examples are finally provided to validate the effectiveness and superiority of the proposed functionals and the obtained results over some existing ones.

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Exponential H∞ Filtering for Continuous-Time Switched Neural Networks Under Persistent Dwell-Time Switching Regularity

Cited by 120 publications

References 39 publications

Finite-Time $\mathcal {L}_{2}$-$\mathcal {L}_{\infty }$ Synchronization for Semi-Markov Jump Inertial Neural Networks Using Sampled Data

Finite-Time $\mathcal {L}_{2}$-$\mathcal {L}_{\infty }$ Synchronization for Semi-Markov Jump Inertial Neural Networks Using Sampled Data

Valve Controller Design of Multi-Machine Power Systems Based on Adaptive Hamilton Minimax Method

Sampled‐data exponential stabilization of switched nonlinear delayed systems with asynchronous switching

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