This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional (LKF) is constructed by introducing a novel augmented term which cont...
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ISBN:
(纸本)9789881563804
This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional (LKF) is constructed by introducing a novel augmented term which contains the derivative of state vector into integral terms. Then the extended reciprocally convex matrix inequality together with the Wirtinger integral inequality is used to estimate the derivative of the proposed LKF. As a result, a stability criterion with less conservatism is established. Finally, the advantage of the stability criterion is demonstrated through a numerical example and the application of the stability criterion to stability analysis of load frequency control is illustrated.
This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional(LKF) is constructed by introducing a novel augmented term which conta...
详细信息
This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional(LKF) is constructed by introducing a novel augmented term which contains the derivative of state vector into integral terms. Then the extended reciprocally convex matrix inequality together with the Wirtinger integral inequality is used to estimate the derivative of the proposed LKF. As a result, a stability criterion with less conservatism is established. Finally, the advantage of the stability criterion is demonstrated through a numerical example and the application of the stability criterion to stability analysis of load frequency control is illustrated.
In this paper, the delay-dependent stability problem of the switched neural networks with time-varying delay is considered. By taking advantage of the average dwell time method and Lyapunov-Krasovskii functional (LKF)...
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In this paper, the delay-dependent stability problem of the switched neural networks with time-varying delay is considered. By taking advantage of the average dwell time method and Lyapunov-Krasovskii functional (LKF) method, and using free-matrix-based integral inequality and the extended reciprocally convex matrix inequality, a less conservative delay-dependent exponential stability criterion in linear matrix inequalities (LMIs) is developed. Two numerical examples are given to demonstrate the benefits of the proposed criterion. (C) 2018 Elsevier B.V. All rights reserved.
The problem of non-fragile control for T-S fuzzy systems with parameter uncertainties is investigated in this paper. The focus is to construct an augmented Lyapunov-Krasovskii functional(LKF), single integral terms ar...
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The problem of non-fragile control for T-S fuzzy systems with parameter uncertainties is investigated in this paper. The focus is to construct an augmented Lyapunov-Krasovskii functional(LKF), single integral terms are processed by the method of an improved reciprocallyconvexinequality and integration by parts, which is derived to a new h(t)-depended stability criteria that finite-time bounded with extended dissipative for the closed-loop system. Furthermore, by using the linear matrix inequalities(LMIs), we can get the desired gain matrices of T-S fuzzy system. It is worth noting that these condition can derive to less conservative results than those existing approaches. And numerical examples are used to demonstrate the feasibility and superiority of the results. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.
The H performance state estimation for static neural networks with time-varying delays is studied in this ***,an augmented Lyapunov-Krasovskii functional（LKF） with the triple integral term and the delay-product-type...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
The H performance state estimation for static neural networks with time-varying delays is studied in this ***,an augmented Lyapunov-Krasovskii functional（LKF） with the triple integral term and the delay-product-type term is ***,a generalized reciprocally convex matrix inequality is employed to deal with the derivative of the *** that,by utilizing the relaxed quadratic function negative-definiteness determination method to dispose of the time derivative of the delay-product-type term,a less conservative state estimation criterion is ***,the effectiveness of the proposed method is shown through a numerical example.
This paper presents an improved stability condition for neural networks with a time-varying ***,an improved Lyapunov-Krasovskii functional(LKF) is constructed by introducing the delay-product term and the augmented **...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
This paper presents an improved stability condition for neural networks with a time-varying ***,an improved Lyapunov-Krasovskii functional(LKF) is constructed by introducing the delay-product term and the augmented ***,a less conservative delay-dependent stability criterion for neural networks with a time-varying delay is established by utilizing the generalized reciprocallyconvex combination and a relaxed quadratic function ***,a numerical example is used to illustrate the merit and effectiveness of the proposed stability criterion.
This paper is concerned with the stabilization problem for T-S fuzzy system with interval time-varying delay. By constructing a novel augmented LKF and using a developed reciprocally convex matrix inequality proposed ...
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ISBN:
(纸本)9781538629185
This paper is concerned with the stabilization problem for T-S fuzzy system with interval time-varying delay. By constructing a novel augmented LKF and using a developed reciprocally convex matrix inequality proposed in this paper to bound the derivative of the LKF, a delay-dependent stabilization condition based on parallel distributed compensation scheme is worked out for the closed-loop fuzzy system. Two numerical examples and an application to control of a truck-trailer are given to illustrate the effectiveness of our method.
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