This paper aims at familiarizing the reader with Stochastic Hybrid Systems (SHSs) and enabling her to use these systems to model and analyze Networked Control Systems (NCSs). Towards this goal, we introduce two different models of SHSs and a set of theoretical tools for their analysis. In parallel with the presentation of the mathematical models and results, we provide a few simple examples tha...

This paper is on production planning and inventory control in systems where manufacturing and remanufacturing operations occur simultaneously. Typical for these hybrid systems is, that both the output of the manufacturing process and the output of the remanufacturing process can be used to fulfil customer demands. Here, we consider a relatively simple hybrid system, related to a single componen...

Robustness of hybrid control systems to measurement noise, actuator disturbances, and more generally perturbations, is analyzed. The relationship between the robustness of a hybrid control system and of its implementations is emphasized. Firstly, a formal definition of implementation of a hybrid control system is provided, based on the uniqueness of the solutions. Then, two examples are analyze...

This paper deals with the synthesis of control software for hybrid systems speciied as hybrid automata. Instead of generating the software from scratch, the synthesis is based on a generic layered software architecture which supports both periodic and event-triggered computations. The use of the layered software architecture as the framework for implementing hybrid controllers is motivated in t...

for Multiple Robotic Mechanisms Martin Buss G unther Schmidt Department of Automatic Control Engineering Technical University of Munich D-80290 M unchen, Germany E-mail: martin/[email protected] This paper is published in the Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems IROS, pp. 140-147, Osaka, Japan, 1996. Abstract In this paper we pro...

Minimize h(x(0), x(1)) subject to dx(t) ∈ F (t, x(t))dt + G(t, x(t))dμ(t) ∀t∈[0, 1] (x(0), x(1)) ∈ C ⊂ IR × IR l(t, x(t)) ≤ 0 ∀t∈[0, 1] dμ ∈ K where h : IR × IR → IR, and l : [0, 1]× IR → IR are given functions, F : [0, 1]× IR → P(IRn), and G : [0, 1] × IR → P(IRn×q) are given set-valued maps, K ⊂ C∗([0, 1];K) is the set of control measures supported on [0, 1] with range in a given set K ⊂ IR, ...