A sliding-mode controller with an integral-operation switching surface is a
dopted to control the position of an induction servo motor drive. Moreover,
to relax the requirement for the bound of uncertainties, a fuzzy neural ne
twork (FNN) sliding-mode controller is investigated, in which the FNN is ut
ilised to estimate the bound of uncertainties real-time. The theoretical an
alyses for the proposed FNN sliding-mode controller are described in detail
. In addition, to guarantee the convergence of tracking error, analytical m
ethods based on a discrete-type Lyapunov function are proposed to determine
the varied learning rates of the FNN. Simulation and experimental results
show that the proposed FNN sliding-mode controller provides high-performanc
e dynamic characteristics and is robust with regard to plant parameter vari
ations and external load disturbance. Furthermore, comparing with the slidi
ng-mode controller, smaller control effort results, and the chattering phen
omenon is much reduced by the proposed FNN sliding-mode controller.