A New Contribution to the Nonlinear Direct Adaptive Inverse Control Based on Volterra Model Subject to Sinusoidal Disturbance

Abstract

This paper aims to perform the performance analysis of the Modified Variable Step Size Fractional Least Mean Square (MVSS-FLMS) algorithm in the design of Direct Adaptive Inverse Control (DAIC) nonlinear based on Volterra model. The motivation for formulating the DAIC based on Volterra model, is so that the controller can track the inverse dynamics of plants with nonlinearity of polynomial type. Since the MVSS-FLMS algorithm proposes the use of variable step size, then its application in nonlinear DAIC design allows to obtain nonconservative results for a performance analysis, with respect to convergence speed and steady-state Mean Square Error (MSE). As an increment of the complexity scenario, the present work was evaluated in the presence of a sinusoidal disturbance signal added to the control signal.