Desacoplamento de um gerador síncrono através de um controle adaptativo por modelo de referência baseado em funções de Base radial

摘要

An alternative nonlinear technique for decoupling and control is presented. This techniqueis based on a RBF (Radial Basis Functions) neural network and it is applied to thesynchronous generator model. The synchronous generator is a coupled system, in otherwords, a change at one input variable of the system, changes more than one output. TheRBF network will perform the decoupling, separating the control of the following outputsvariables: the load angle and flux linkage in the field winding. This technique does notrequire knowledge of the system parameters and, due the nature of radial basis functions,it shows itself stable to parametric uncertainties, disturbances and simpler when it is appliedin control. The RBF decoupler is designed in this work for decouple a nonlinearMIMO system with two inputs and two outputs. The weights between hidden and outputlayer are modified online, using an adaptive law in real time. The adaptive law is developedby Lyapunov s Method. A decoupling adaptive controller uses the errors betweensystem outputs and model outputs, and filtered outputs of the system to produce controlsignals. The RBF network forces each outputs of generator to behave like referencemodel. When the RBF approaches adequately control signals, the system decoupling isachieved. A mathematical proof and analysis are showed. Simulations are presented toshow the performance and robustness of the RBF network