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Reseña del editor Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems.Borrowing from BiologyExamining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts.Progressive DevelopmentAfter an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware.Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.
Discrete neural network control springerlink zhang j ge ss lee th 2002 direct rbf neural network control of a class of discretetime nonaffine nonlinear systems in proceedings of the american control conference pp 424429 google scholar
Neural network control of nonlinear discretetime systems therefore first a novel nncs representation incorporating the system uncertainties and network imperfections are derived in this chapter subsequently an online neural network nn identifier is developed to identify the control coefficient matrix of the stochastic nonlinear discretetime system for the purpose of the controller design
Neural network control of nonlinear discretetime systems neural network control of nonlinear discretetime systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations stability analysis and computer simulations
Neural network control of nonlinear discrete time systems neural network control of nonlinear discrete time systems by jagannathan sarangapani neural network control of nonlinear discrete time systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems features
Neural networkbased control of nonlinear discretetime operations research systems engineering and industrial engineering commons recommended citation j sarangapani et al neural networkbased control of nonlinear discretetime systems in nonstrict form proceedings of the 44th ieee conference on decision and control and the european control
Neural network control of nonlinear discretetime systems promoção válida até 07062020 apenas para livros nacionais e importados exceto didáticos cursos e idiomas dicionários mega saldão e outlet
Crc neural network control of nonlinear discrete time file crcneuralnetworkcontrolofnonlineardiscretetimesystemsapr2006pdf0824726774pdf