In this article, the ${H}_{infinity }$ bipartite synchronization issue is studied for a class of discrete-time coupled switched neural networks with antagonistic interactions via a distributeddynamicevent-triggered ...
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In this article, the ${H}_{infinity }$ bipartite synchronization issue is studied for a class of discrete-time coupled switched neural networks with antagonistic interactions via a distributeddynamicevent-triggered control scheme. Essentially different from most current literature, the topology switching of the investigated signed graph is governed by a double-layer switching signal, which integrates a flexible deterministic switching regularity, the persistent dwell-time switching, into a Markov chain to represent the variation of transition probability. Considering the coexistence of cooperative and antagonistic interactions among nodes, the bipartite synchronization of which the dynamics of nodes converge to values with the same modulus but the opposite signs is explored. A distributed control strategy based on the dynamicevent-triggeredmechanism is utilized to achieve this goal. Under this circumstance, the information update of the controller presents an aperiodic manner, and the frequency of data transmission can be reduced extensively. Thereafter, by constructing a novel Lyapunov function depending on both the switching signal and the internal dynamic nonnegative variable of the triggering mechanism, the exponential stability of bipartite synchronization error systems in the mean-square sense is analyzed. Finally, two simulation examples are provided to illustrate the effectiveness of the derived results.
This paper addresses the event-triggered secondary control problem for islanded microgrid with disturbances. Adaptive distributed control law is proposed for regulating voltage and frequency to desired values, while a...
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This paper addresses the event-triggered secondary control problem for islanded microgrid with disturbances. Adaptive distributed control law is proposed for regulating voltage and frequency to desired values, while avoiding using global information. A novel distributed adaptive dynamicevent-triggering mechanism (DETM) is proposed, the adaptive parameters are incorporated into the ETM design, such that not only strictly positive minimum event-triggering interval (METI) can be guaranteed, even in the presence of disturbances, but also global information is not required for implementation of the ETM. By means of auxiliary function, a novel Lyapunov function is constructed for stability analysis and ETM design. Compared with the existing results, with the proposed event-triggered control strategy, strictly positive METI and no dependence on global information can be achieved simultaneously. Moreover, the proposed adaptive event-triggered control strategy is robust to external disturbances. Finally, the effectiveness of the proposed method is verified by simulation results.
This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzz...
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This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.
This article discusses the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy asynchronous controller design problem for nonlinear multiagent systems via a dynamicevent-triggered scheme in the discrete-time context. To ...
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This article discusses the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy asynchronous controller design problem for nonlinear multiagent systems via a dynamicevent-triggered scheme in the discrete-time context. To formulate the asynchronous phenomena between the system modes and the anticipant controller modes, the hidden Markov model is proposed. The primary attention is focused on the explicit design of the dynamicevent-triggered strategy that can be dynamically adjusted in line with system information, which mitigates the communication burden efficiently. On this occasion, the information renewal of the controller is aperiodic. Furthermore, the nonlinear characteristics are effectually disposed through utilizing a unique IT2 T-S fuzzy model, which is with mismatched membership functions (MFs). As a result, the resulting closed-loop fuzzy multiagent systems are accompanied by mismatched MFs and asynchronous modes, whereafter, via solving the convex optimization problem, the desired controller gains are acquired. eventually, the validity and practicability of the developed control scheme are illustrated by two examples.
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