On disturbance rejection in nonlinear control

In a recent paper of Mukhopadhyay and Narendra (1993), the problem of disturbance rejection in the control of nonlinear systems with additive disturbance generated by some unforced dynamical systems was formulated and solved by using neural networks for several models of varying complexity. It is the purpose of this paper to generalize this result to more general systems where the disturbance is not necessarily additive, and to provide theoretical justification to the existence of solution. Direct training of implicit function controller is also discussed.