A discrete-time periodic adaptive control for systems in the presence of nonsector nonlinearities

A new periodic least-squares estimator with nonlinear data weighting is developed and used to design a periodic adaptive control for a simple discrete-time nonlinear system in the presence of time-varying parametric uncertainties. A global stability result is obtained through Lyapunov analysis without assuming any growth conditions on the nonlinearities. Simulation results further confirm the effectiveness of the presented methods.