On-line approximation based robust adaptive control for a class of uncertain systems

Three kinds of approximators are widely used in adaptive controllers for the nonlinear systems with uncertainty. They are neural network, fuzzy logic systems and wavelet approximator, respectively. By unifying these three approximators, we developed an on-line approximation based controller for a class of uncertain nonlinear systems. It is proved that with the proposed control law and update laws, the closed-loop system is guaranteed to be stable and the tracking error converges to zero in the presence of unknown nonlinearity. A simulation example is presented to demonstrate the method.