Observer-based adaptive neural control of uncertain MIMO nonlinear systems with unknown control direction

This paper investigates adaptive neural network output feedback control for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with an unknown sign of control gain matrix. Because the system states are not required to be available for measurement, an observer is designed to estimate thesystem states. In order to deal with the unknown sign of control gain matrix, the Nussbaum-type function is utilized. By using neural network, we approximated the unknown nonlinear functions and perfectly avoided the controller singularity problem. The stability of the closed-loop system is analyzed by using Lyapunov method. Theoretical results are illustrated through a simulation example. Copyright (c) 2012 John Wiley & Sons, Ltd.