Title: A separation principle for nonlinear systems (1 hour)
Abstract: This talk introduces a ``state-variable approach'' to output feedback stabilization of nonlinear systems which, unlike other recently developed techniques, does not work in input-output coordinates and does not rely on input saturation to achieve separation between the state feedback and observer designs. Rather, we show that by using nonlinear high-gain observers working in state coordinates, together with a dynamic projection algorithm, the same kind of separation principle is achieved for a larger class of systems which are not uniformly completely observable. By working in state coordinates, this approach avoids using knowledge of the inverse of the observability mapping to estimate the state of the plant, which is otherwise needed when using high-gain observers to estimate the output time derivatives.