A multi-model parameter and state estimation of mechanical systems

A parametric neural model and an identification learning algorithm for systems parameter and state estimation are described. For a complex nonlinear plants identification, a fuzzy-neural multi-model approach, is proposed. The proposed multi-model contains two parametric neural models, which are applied for real-time identification of a nonlinear mechanical system with friction. The simulation and experimental results confirms the multi-model applicability.