Abstract
Several explicit algorithms for tracking the parameters of second order models have been derived by the authors based on information available from the system time trajectory. In this paper the problem is recast in terms of recurrent integral-hybrid networks used in a hierarchical formation for both the reduced order model and to estimate the derivatives for parameter tracking. We relax the constant parameter condition by assuming linear time variation, the additional information is extracted from the system output trajectory by obtaining higher time derivatives which result in explicit functions to track the parameters online.