1,720,979 research outputs found
Optimal neural feedback control applied to a problem of economic growth in freight transportation market
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Sliding-mode state estimation for a class of multi-output nonlinear continuous-time systems
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Identification of freeway macroscopic models using information from mobile phones
No full textA method for the identification of a freeway macroscopic model is presented. The model is based on the idea of dividing a freeway trunk in sections covered by the cells of the wireless network and associated with state variables describing density of vehicles, mean velocity, and percentage of active mobile phones. Using the density and hand-off measurements from the cellular network, the parameters of such model are identified via an algorithm based on stochastic approximation. Successful simulation results are reported and discusse
An approximate solution to optimal Lp state estimation problems
No full textWe consider optimal estimation problems characterized by a state vector with i) dynamics described via a differential equation with Lipschitz nonlinearities, ii) partial information provided via a Lipschitz nonlinear mapping, and iii) an Lp norm measure of the estimation error to be minimized. An approximate solution of such optimal estimation problem is searched for by restricting the optimization to parameterized nonlinear approximators such as feedforward neural networks. The parameters of a feedforward neural network are the neural weights. This approach entails a constrained nonlinear programming problem, whose constraints are given by the dynamic and measurement equations, and the conditions guaranteeing the stability of the estimation error. To optimize the parameters values of neural networks an algorithm is developed that is based on appropriate sampling of the state and error spaces. Choices of the sample points are devised based on the notion of dispersion, which allow one to obtain an approximate solution of the optimal estimation problem by a small sample complexity. © 2005 AACC
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