  In this paper, based on real-time nonlinear receding horizon control
methodology, a novel approach is developed for parameter estimation of time
invariant and time varying nonlinear dynamical systems in chaotic environments.
Here, the parameter estimation problem is converted into a family of finite
horizon optimization control problems. The corresponding receding horizon
control problem is then solved numerically, in real-time, without recourse to
any iterative approximation methods by introducing the stabilized continuation
method and backward sweep algorithm. The significance of this work lies in its
real-time nature and its powerful results on nonlinear chaotic systems with
time varying parameters. The effective nature of the proposed method is
demonstrated on two chaotic systems, with time invariant and time varying
parameters. At the end, robustness performance of the proposed algorithm
against bounded noise is investigated.
