TY - JFULL AU - J. Fernandez de Canete and S. Gonzalez-Perez and P. del Saz-Orozco and I. Garcia-Moral PY - 2008/6/ TI - Robust Stability in Multivariable Neural Network Control using Harmonic Analysis T2 - International Journal of Electrical and Computer Engineering SP - 1416 EP - 1421 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/15936 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 17, 2008 N2 - Robust stability and performance are the two most basic features of feedback control systems. The harmonic balance analysis technique enables to analyze the stability of limit cycles arising from a neural network control based system operating over nonlinear plants. In this work a robust stability analysis based on the harmonic balance is presented and applied to a neural based control of a non-linear binary distillation column with unstructured uncertainty. We develop ways to describe uncertainty in the form of neglected nonlinear dynamics and high harmonics for the plant and controller respectively. Finally, conclusions about the performance of the neural control system are discussed using the Nyquist stability margin together with the structured singular values of the uncertainty as a robustness measure. ER -