Titlebook: Hybrid Systems: Computation and Control; 8th International Wo Manfred Morari,Lothar Thiele Conference proceedings 2005 Springer-Verlag Berl

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A Homology Theory for Hybrid Systems: Hybrid Homologyhieved by considering the underlying “space” of a hybrid system—its . or .. The homotopy colimit can be applied to this H-space to obtain a single topological space; the hybrid homology of an H-space is the homology of this space. The result is a spectral sequence converging to the hybrid homology o

Intuitive

Controller Synthesis on Non-uniform and Uncertain Discrete–Time Domainsidered. This class of problems is relevant to many application domains. For instance, in engine control a heterogenous and, to some extent, uncertain event–driven time domain is due to the behavior of the 4-stroke internal combustion engine, with which the controller has to synchronize to operate th

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Optimal Control of Discrete Hybrid Stochastic Automataoducing a suitable hybrid model called Discrete Hybrid Stochastic Automaton (DHSA), different finite-time optimal control approaches are examined: (1) Stochastic Hybrid Optimal Control (SHOC), that “optimistically” determines the trajectory providing the best trade off between the tracking performan

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Hybrid Decentralized Control of Large Scale Systems control problems. In particular we show that a formation flight problem, a paper machine control problem and the coordination of cameras in a monitoring network can be cast into this class. In the second part of the paper we propose a decentralized control scheme to tackle the complexity of the pro

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Position and Force Control of Nonsmooth Lagrangian Dynamical Systems Without Frictionntacts such as supposing that they are permanent. We’re interested here in having a look at what happens when no such assumptions is made: we are led therefore to propose a Lyapunov stability analysis of a position and force control law in the mathematical framework of nonsmooth Lagrangian dynamical

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Existence of Cascade Discrete-Continuous State Estimators for Systems on a Partial Orderation error is bounded by a monotonically nonincreasing function of the discrete state estimation error, with both the estimation errors converging to zero. This work shows that the lattice approach to estimation is general as the proposed estimator can be constructed for any observable and discrete