Dynamical reconstruction of unknown inputs in nonlinear differential equations Original Research Article

We present an algorithm for the identification of an unknown but bounded input to a nonlinear finite-dimensional system, based on observations taken at discrete time instants and corrupted by observation errors. This algorithm is stable with respect to observation and computational errors. If we have the further information that the unknown input is a signal of bounded variation, then we can give explicit convergence estimates of the algorithm.