8 research outputs found

    Stability of interconnected impulsive systems with and without time-delays using Lyapunov methods

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    In this paper we consider input-to-state stability (ISS) of impulsive control systems with and without time-delays. We prove that if the time-delay system possesses an exponential Lyapunov-Razumikhin function or an exponential Lyapunov-Krasovskii functional, then the system is uniformly ISS provided that the average dwell-time condition is satisfied. Then, we consider large-scale networks of impulsive systems with and without time-delays and we prove that the whole network is uniformly ISS under a small-gain and a dwell-time condition. Moreover, these theorems provide us with tools to construct a Lyapunov function (for time-delay systems - a Lyapunov-Krasovskii functional or a Lyapunov-Razumikhin function) and the corresponding gains of the whole system, using the Lyapunov functions of the subsystems and the internal gains, which are linear and satisfy the small-gain condition. We illustrate the application of the main results on examples

    Application of the LISS Lyapunov-Krasovskii small-gain theorem to autonomously controlled production networks with time-delays

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    In this paper we consider general autonomously controlled production networks. A production network consists of geographically distributed plants, which are connected by transport routes such that transportation times (time-delays) have to be taken into account. In autonomous controlled production networks logistic objects (e.g., parts, orders) route themselves through a network based on local information. In this paper these kinds of logistic networks are investigated in view of stability to avoid negative outcomes such as high inventory costs or loss of customers. We use the local inputto- state stability (LISS) property and the tool of an LISS Lyapunov-Krasovskii functional for the stability investigation. By the application of the LISS Lyapunov-Krasovskii small-gain theorem we derive conditions, which guarantee stability of the production network
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