ABSTRACT
This chapter deals with adaptive trajectory tracking for a class ofMIMOdiscrete-time
nonlinear systems in the presence of bounded disturbances. A recurrent high order
neural network is first used to identify the plant model, then based on this neural
model, a discrete-time control law, which combines discrete-time block control and
sliding mode techniques, is derived. The chapter also includes the respective stability
analysis for the whole system. A strategy is also proposed to avoid zero-crossing
of specific adaptive weights. Applicability of the proposed scheme is illustrated via
simulation of a discrete-time nonlinear controller for an induction motor.
