Hierarchical Parameter and State Estimation of Fractional Nonlinear Systems

The presented work treats the identification problem for a fractional nonlinear system, especially the fractional-order Hammerstein system starting from measurement data. Using the hierarchical principle, a Kalman-Filter-Based-Least-Squares algorithm is developed to determine the system states and the system parameters. The simulation example prove the efficacy of the algorithm.