Adaptive neural network tracking control for a class of MIMO nonlinear systems with measurement error

An adaptive neural network tracking controller is designed, capable of stabilizing multi-input multi-output nonlinear, affine in the control dynamical systems with measurement error. Uniform ultimate boundedness of the tracking error of the actual system state is guaranteed, as well as boundedness of all other signals in the closed loop. Possible division by zero is avoided with the use of a novel resetting procedure, capable of guaranteeing the boundedness away from zero of certain signals.