Output feedback tracking control for a class of uncertain nonlinear MIMO systems using neural network

An output feedback tracking control algorithm using neural network for a class of uncertain affine nonlinear MIMO systems with external disturbances is presented under the constraints that only the system output variables can be measured. No state observer or additional low-pass filter is employed in the algorithm to make the estimation error dynamics strictly-positive-real(SPR). Only the output error is used in control laws and weights-update laws. The additional robust control term suppresses the influence of external disturbances and the cross-coupling of subsystems, and eliminates the neural network approximation error. The stability of the closed-loop system and the boundedness of signals are also demonstrated by Lyapunov stability theorem. A simulation example demonstrates the feasibility of the proposed approach.