Learning-Based Nonlinear State Estimation With Unknown System Dynamics
Accurate system dynamics are often difficult to obtain in practical industrial processes, which limits the applicability of model-based state estimators. This paper proposes a novel learning-based nonlinear state estimation method for systems with an unknown state equation. A stochastic configuration network is trained...