Adaptive Observers and Parameter Estimation for a Class of Systems Nonlinear in the Parameters

We consider the problem of asymptotic reconstruction of the state and parameter values in systems of ordinary differential equations. A solution to this problem is proposed for a class of systems of which the unknowns are allowed to be nonlinearly parameterized functions of state and time. Going beyond the concept of asymptotic Lyapunov stability, we provide for this class a reconstruction technique based on the notions of weakly attracting sets and non-uniform convergence. Reconstruction of state and parameter values is subjected to persistency of excitation conditions. In absence of nonlinear parametrization the resulting observers reduce to standard estimation schemes. This allows to view the proposed method as a generalization of the conventional canonical adaptive observer design.