Guangming Zhuang

Delay-dependent stability and dissipativity analysis of generalized neural networks with Markovian jump parameters and two delay components

Abstract This paper focuses on the problem of delay-dependent stability and dissipativity analysis of generalized neural networks (GNNs) with Markovian jump parameters and two delay components. By constructing novel augmented Lyapunov–Krasovskii functional (LKF), using free-matrix-based inequality to estimate the derivative of Lyapunov function and employing the reciprocally convex approach to consider the relationship between the time-varying delay and its interval, some improved delay-dependent stability criteria and dissipativity criteria are established in terms of linear matrix inequalities. Moreover, the obtained criteria is extended to analyze the stability analysis of GNNs with two delay components and the passivity analysis of GNNs with one delay. Numerical examples are given to show the effectiveness and the significant improvement of the proposed methods.

Adaptive decentralized NN control of large-scale stochastic nonlinear time-delay systems with unknown dead-zone inputs

In this paper, the problem of adaptive decentralized neural network (NN) control for a class of large-scale stochastic nonlinear time-delay systems with unknown dead-zone inputs is investigated. Neural networks are utilized to approximate unknown nonlinear functions, and an adaptive decentralized controller is constructed by incorporating the minimal learning parameters algorithm into backstepping design procedure. It is proved that the proposed control scheme guarantees that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded in probability. Finally, a numerical example is provided to demonstrate the effectiveness of the present results.

Improved passivity analysis for neural networks with Markovian jumping parameters and interval time-varying delays

The problem of passivity analysis for neural networks with Markovian jumping parameters and interval time-varying delays is investigated in this paper. By constructing a novel Lyapunov-Krasovskii functional based on the complete delay-decomposing idea and using reciprocally convex technique, some improved delay-dependent passivity criteria are established in terms of linear matrix inequalities. Numerical examples are also given to show the effectiveness of the proposed methods.

Non-fragile finite-time extended dissipative control for a class of uncertain discrete time switched linear systems

Abstract In this paper, the issues of finite-time extended dissipative analysis and non-fragile control are investigated for a class of uncertain discrete time switched linear systems. Based on average dwell-time approach, sufficient conditions for the finite-time boundedness and finite-time extended dissipative performance of the considered systems are proposed by solving some linear matrix inequalities, where using the concept of extended dissipative, we can solve the H∞, L 2 − L ∞ , Passivity and (Q, S, R)-dissipativity performance in a unified framework. Furthermore, two form of non-fragile state feedback controllers are designed to guarantee that the closed-loop systems satisfy the finite-time extended dissipative performance. Finally, simulation example is given to show the efficiency of the proposed methods.

Improved delay-dependent stabilization for a class of networked control systems with nonlinear perturbations and two delay components

Abstract This paper focuses on the problem of delay-dependent state feedback control for a class of networked control systems (NCSs) with nonlinear perturbations and two delay components. Based on the dynamic delay interval (DDI) method and the Wirtinger integral inequality, some improved delay-dependent stability analysis are obtained. Furthermore, the results are extended to the conditions of NCSs with one time delay, and the corresponding stability analysis results and state feedback controller are obtained. Finally, some numerical examples and simulations are given to show the effectiveness of the proposed methods.

Nonfragile Finite-Time Extended Dissipative Control for a Class of Uncertain Switched Neutral Systems

This paper is concerned with finite-time extended dissipative analysis and nonfragile control for a class of uncertain switched neutral systems with time delay, and the controller is assumed to have either additive or multiplicative form. By employing the average dwell-time and linear matrix inequality technique, sufficient conditions for finite-time boundedness of the switched neutral system are provided. Then finite-time extended dissipative performance for the switched neutral system is addressed, where we can solve ,, Passivity, and ()-dissipativity performance in a unified framework based on the concept of extended dissipative. Furthermore, nonfragile state feedback controllers are proposed to guarantee that the closed-loop system is finite-time bounded with extended dissipative performance. Finally, numerical examples are given to demonstrate the effectiveness of the proposed method.

ℓ 2 gain analysis and state feedback stabilization of switched systems with multiple additive time-varying delays

Abstract This paper focuses on the problem of l 2 gain analysis and state feedback stabilization for a class of switched systems with multiple additive time-varying delays. First, a new model about switched systems with multiple additive time-varying delays is given. Then, based on the extended dynamic delay interval (EDDI) method, we construct a new multiple Lyapunov function. Combing average dwell-time method, reciprocally convex combination technique and Wirtinger interval inequality to estimate the bounding of the integral term, the stability criteria and l 2 gain performance of switched systems are given. At last, based on the stability results, the state feedback stabilization problem of the switched systems is studied. The results of sufficient conditions are shown in terms of linear matrix inequalities (LMIs). Numerical examples are provided to show the effectiveness of the proposed methods.

Command filtered backstepping tracking control of uncertain nonlinear strict-feedback systems under a directed graph

This paper studies the distributed consensus tracking control problem of multiple uncertain non-linear strict-feedback systems under a directed graph. The command filtered backstepping approach is utilised to alleviate computation burdens and construct distributed controllers, which involves compensated signals eliminating filtered error effects in the design procedure. Neural networks are employed to estimate uncertain non-linear items. Using a Lyapunov stability theorem, it is proved that all signals in the closed-looped systems are semi-globally uniformly ultimately bounded. In addition, consensus errors converge to a small neighbourhood of the origin by adjusting the appropriate design parameters. Finally, simulation results are presented to demonstrate the effectiveness of the developed control design approach.

Neural-network-based distributed adaptive synchronization for nonlinear multi-agent systems in pure-feedback form

In this paper, the problem of distributed adaptive synchronization for unknown nonlinear multi-agent systems in pure-feedback form is studied under a directed graph. Neural networks are used to approximate the unknown nonlinear dynamics, and by incorporating the dynamic surface control (DSC) technique into backstepping design procedure, distributed adaptive consensus controllers are developed. A novel method is given for reducing the burden of networked communication. It is shown that the proposed distributed consensus controllers guarantee that all signals in the closed-loop system are cooperatively semi-globally uniformly ultimately bounded, and the consensus errors converge to a small neighborhood of the origin. Finally, a simulation example is given to show the effectiveness of the designed control scheme.

Admissibility and stabilization of stochastic singular Markovian jump systems with time delays

Abstract This paper deals with the admissibility analysis and stabilization of stochastic singular Markovian jump systems (SSMJSs) with time delays. More general conditions for the existence and uniqueness of the impulse-free solution to delayed SSMJSs are presented. Consequently, by constructing stochastic Lyapunov–Krasovskii functional and applying generalized Ito formula, new sufficient conditions for the stability of SSMJSs and delayed SSMJSs are obtained in terms of strict linear matrix inequalities. State feedback controller is designed to ensure stabilization of the delayed SSMJSs. Three illustrative examples, including an R L C circuit network and an oil catalytic cracking process, are employed to verify the effectiveness and usefulness of the obtained results.