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The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. It provides solutions for the output trajectory tracking problem of unknown nonlinear systems based on sliding modes and inverse optimal control scheme.
This comprehensive book addresses the modeling and design of controllers for the doubly fed induction generator (DFIG) used in wind energy applications. Focusing on the use of nonlinear control techniques, the text discusses the main features and advantages of the DFIG, describes key theoretical fundamentals and the DFIG mathematical model, and develops controllers using inverse optimal control, sliding modes, and neural networks. It also devises an improvement to add robustness in the presence of parametric variations, as well as details the results of real-time implementations.
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