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This article focuses on static output feedback control for fuzzy Markovian switching singularly perturbed systems (FMSSPSs) with deception attacks and asynchronous quantized measurement output. Different from the previous work, both the logarithmic quantizer and the static output feedback controller are dependent on the operation system; by means of hidden Markov models, their modes run asynchronously with that of FMSSPSs. Additionally, the deception attacks are guided by a Bernoulli variable, and nonlinear characteristics are modeled by the Takagi-Sugeno fuzzy model. By resorting to a mode-dependent Lyapunov functional, several criteria are acquired and strictly (Q, S , R)-γdissipative of FMSSPSs can be ensured. Finally, a dc motor model is expressed to illustrate the effectiveness of the asynchronous control scheme.

This paper proposes a novel nonfragile robust asynchronous control scheme for master-slave uncertain chaotic Lurie network systems with randomly occurring time-varying parameter uncertainties and controller gain fluctuation. The asynchronous phenomenon occurs between the system modes and the controller modes. In order to consider a more realistic situation in designing a reliable proportional-derivative controller, Bernoulli stochastic process and memory feedback are introduced to the concept of nonlinear control system. First, by taking full advantage of the additional derivative state term and variable multiple integral terms, a newly augmented Lyapunov-Krasovskii functional is constructed via an adjustable parameter. Second, based on new integral inequalities including almost all of the existing integral inequalities, which can produce more accurate bounds with more orthogonal polynomials considered, less conservative synchronization criteria are obtained. Third, a desired nonfragile estimator controller is achieved under the aforementioned methods.Finally, 4 numerical simulation examples of Chua's circuit and 3-cell cellular neural network with multiscroll chaotic attractors are presented to illustrate the effectiveness and advantages of the proposed theoretical results.

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This article investigates exponential synchronization for complex dynamical networks (CDNs) with nonfragile sampled-data feedback control. An important yet challenging problem that contains the time delays of the controller, the uncertainties occurrence and randomness of controller gain fluctuation due to the packet loss, and time delays during data transmission is to be solved. A novel Lyapunov-Krasovskii functional (LKF) that allows for more free matrix terms and slacks certain one of the terms to nonpositive definite is first constructed based upon special refined block matrices. By employing the novel LKF and functional analysis theory, the nonfragile sampled-data feedback controller is developed to guarantee the exponential synchronization of CDNs and make a more optimal bound estimation of the sampled period. Finally, compared simulation examples are performed as significant to demonstrate the effective performance and the superiority of the proposed methods.