Observer‐based guaranteed cost control for IT‐2 stochastic fuzzy coupled neural networks with Markov switching topology

Abstract

SummaryThis 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.