Adaptive control of nonlinear, uncertain systems using local function estimation

An adaptive control scheme is proposed for controlling a certain class of n onlinear, uncertain systems. When a local approximation of the system funct ion using its Taylor's expansion is possible, this scheme provides an adapt ation law to estimate such an approximation. With a proper sampling rule, t he neighborhood of approximation can be moved from time to time in order to capture the fast changing system dynamics. Practical implementation issues are also considered to avoid exciting the unmodeled dynamics, to reduce th e noise sensitivity, and accommodate the various signal levels in the syste m response. The important features and performance of the proposed controll er are illustrated through simulations and experimental results associated with a magnetic bearing system.