Summary This study focuses on the guaranteed cost control problem for interval type‐2 stochastic fuzzy coupled neural networks (NNs) elicited by the observer framework with Markov switching topology, external disturbances, and quantization effect. In particular, the guaranteed cost controller is developed with an upper bound of the guaranteed cost function and also ensures stability of the addressed networks. Also, the integration of lower and upper membership functions are incorporated to relax the stability condition of the networks. Notably, the randomness phenomena are incorporated by the agency of stochastic variables that satisfies the Bernoulli distribution characteristics. Specifically, the state feedback controller considered with quantization effect is designed through undirected communication graph subject to Markov switching topology. In consequence with Lyapunov–Krasovskii‐functional and algebraic graph theory, sufficient conditions are established to assure the stochastic stabilization of the NNs with some specified cost value. Explicitly, the optimal upper bound of the guaranteed cost function and the controller gain fluctuations of the state and the observer are effectuated through the developed conditions. Finally, the reduced conservatism and efficiency of the proposed analytical design are demonstrated through a numerical example.

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This study inspects the problem of fault‐tolerant control based filter design for interval type‐2 (IT‐2) fuzzy systems with deception attacks and missing measurements, under hybrid‐triggered mechanism. At first, hybrid‐triggered mechanism is commenced to preserve the network bandwidth and also to maintain the competent system performance. Next, the existence of deception attack in the filter infuses unwanted data in the measurement output in order to limit the transmitted signal in the communication networks. The behaviors of triggering mechanism and attack signals are governed by stochastic Bernoulli distribution. Moreover, the missing measurements phenomenon is also characterized by stochastic random variables, which observes the data loss between system and the filter during the transference of information. The sensor failure, deception attack and missing measurement are the key factors that will destruct the network security completely. Further, by endowing Lyapunov stability theory and linear matrix inequality (LMI), a set of adequate conditions is fabricated to ensure the mean‐square asymptotic filtering of the proposed IT‐2 fuzzy system. Subsequently, the filter gain matrices are exhibited with desired LMI conditions. Eventually, the capability and usefulness of the proposed fault‐tolerant filter scheme is substantiated via two numerical examples which includes a tunnel diode application.