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The problem of generalized dissipative state estimation for discrete-time nonhomogeneous semi-Markov jump nonlinear systems is concerned in this paper. In this paper, we consider the semi-Markov renewal chain is nonhomogeneous and the states of the system are inaccessible. The aim of this paper is to propose the estimator-designed method to ensure that the system is σ -mean-square stable and satisfy extended dissipative performance. By using the semi-Markov kernel method and polytopic approach, and constructing a new type of Lyapunov function, which not only depends on the sojourn-time but also on the stochastic switching rules, the state estimator gains can be obtained. At last, a numerical example is adopted to verify the superiority of the presented control strategy. [ABSTRACT FROM AUTHOR]

In this study, a class of finite-time consensus of multiple transmission control protocol/active queue management (TCP/AQM) networks is investigated on the basis of a design idea of multi-agent systems, and for the first time, to our knowledge, a novel congestion control concept with neural networks is proposed. First, the problem statement and design goal of the consensus of multiple TCP/AQM networks is given. Then, a pre-assigned finite-time function is introduced to ensure that the tracking error approaches a pre-defined area within finite time. Furthermore, by combining a barrier Lyapunov function and backstepping technique, a neural network-based distributed adaptive finite-time control protocol for the output consensus of multiple TCP/AQM networks is presented, which can effectively generate the desired controls and ensure that the convergent time of all errors has nothing to do with the initial condition and design parameters. In addition, all signals in the closed-loop system are bounded. Finally, an example is given to further illustrate the effectiveness of the theoretical finding presented. [ABSTRACT FROM AUTHOR]

This paper intends to focus on the anti-disturbance synchronization issue for genetic regulatory networks subject to reaction-diffusion terms based on the Takagi-Sugeno fuzzy model. In view of the fact that disturbances are widespread in actual control engineering, the stability of the aforementioned systems would be affected, therefore, ensuring the stability of closed-loop genetic regulatory networks is the main goal of this paper. The unknown disturbances are supposed to be generated by an exogenous system, which can be estimated by developing disturbance observers. Furthermore, integrating the disturbance observers with fuzzy rule-based conventional control laws, a new anti-disturbance control strategy is proposed to reject the disturbances and guarantee the desired dynamic performances. Then, by constructing a proper Lyapunov function and using advanced decoupling techniques, some sufficient conditions in the form of linear matrix inequalities, to guarantee the asymptotic stability of the error system, are obtained. Finally, an illustrated example is presented to demonstrate the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

For continuous-time semi-Markov jump neural networks with singularly perturbations, this work deals with the issue of mixed passive and H ∞ non-fragile state estimation. In view of the multiple-time-scales phenomenon that the dynamic behavior of the neural networks may present, the neural networks are interpreted as singularly perturbed systems. Meanwhile, a singular perturbation parameter, i.e., ε, is employed to describe the degree of separation of the fast and the slow states of the system. In order to enhance the tolerance of the estimator when facing gains variations, the non-fragility as a key factor is directly considered in the process of the expected estimator design. Afterwards, relying on the aforementioned considerations, by constructing the ε-dependent Lyapunov function, new sufficient conditions are deduced to ensure the existence of the available non-fragile state estimator. Finally, the superiority of the proposed method is verified by an illustrated example. [ABSTRACT FROM AUTHOR]