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Titlebook: Stability and Stabilization of Nonlinear Systems; Dirk Aeyels (Professor),Françoise Lamnabhi-Lagarri Conference proceedings 1999 Springer-

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Invariant tracking and stabilization: problem formulation and examples,ch that the closed-loop dynamics is invariant under the action of a given group. Errors are then defined as invariants of the group under consideration. The approach is illustrated on two classical examples: the nonholonomic car and a continuous stirred chemical reactor. In both cases the differenti
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A novel impedance grasping strategy as a generalized hamiltonian system,ques presented in [.]. It is shown that robot control design synthesized as a spatial interconnection between the robot and the controller can be easily handled. The idea is based on what is called the . [.] and can be used both for tips grasp and full grasp. One of the major advantages of the prese
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A nonsmooth hybrid maximum principle,g the reference trajectory and yields an adjoint equation of the usual kind, while the second one only requires approximability to first order by Lipschitz maps, and yields an adjoint differential inclusion involving a generalized gradient of the approximating Hamiltonian
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Stabilization by sampled and discrete feedback with positive sampling rate,re stabilization is possible using a fixed positive sampling rate, i.e. where the intersampling times do not tend to zero. A complete characterization of these cases is given for systems with certain homogenity properties
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Linear controllers for tracking chained-form systems,ying state feedback controller with an observer for the chained-form system. For the stability analysis of the “certainty equivalence type” of controller we use a cascaded systems approach. The resulting closed loop system is globally .-exponentially stable
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A novel impedance grasping strategy as a generalized hamiltonian system,ly handled. The idea is based on what is called the . [.] and can be used both for tips grasp and full grasp. One of the major advantages of the presented strategy is the passive nature of the algorithm and the physical intuition it supplies due to the description of the controller as a spatial interconnection of physical elements
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