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

Abstract

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.

Hybrid‐triggered based reliable filter design for interval type‐2 fuzzy system under deception attacks and missing measurements

“…where, Λ > 0 is a positive definite matrix, j = 1, 2, … , 𝜌 ∈ [0, 1), y((k + j)h) denotes the latest sampled data and y(kh) specifies the newest data delivered. The latest sampled signal y((k + j)h) does not depend on (7) and it reaches by exceeding certain threshold in (7). Hence, as a matter of fact that the interval…”

Quantized output feedback resilient control of uncertain systems under hybrid cyber attacks

“…(2) In this article, the system uncertainty and the fluctuation of the controller gain are considered. Compared with the traditional guaranteed cost control, [23][24][25][26][27][28] the influence of a series of signal disturbances such as voltage fluctuation and mechanical wear in the transmission process on the controller gain is rarely considered. The resilient controller proposed for these problems in the running process of the uncertain system will have better practical applicability.…”

“…In recent years, ensuring a certain level of performance without losing stability has become the common goal of many scientific researchers. The guaranteed cost control strategies proposed in many literatures provide us with a more complete design idea 24‐28 . On the one hand, because of the excellent controllability of the method, the stability of the system can be guaranteed.…”

“…At present, good results have been achieved. For example, the guaranteed cost control problem of fuzzy coupled neural network caused by the observer framework with Markov switching topology and external disturbances is studied in Reference 24. Robust guaranteed cost control for polytopic parameter uncertain systems is studied in Reference 26.…”

“…The guaranteed cost control strategies proposed in many literatures provide us with a more complete design idea. [24][25][26][27][28] On the one hand, because of the excellent controllability of the method, the stability of the system can be guaranteed. On the other hand, the upper limit of system performance index is given, so that the system will be constrained by the specified upper limit during operation.…”