In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...

This paper proposes a new robust Kalman filter algorithm under outliers and system uncertainties. The robust Kalman filter of Durovic and Kovacevic is extended to include unknown-but-bounded parameter uncertainties in the state or observation matrix. We first formulate the robust state estimation problem as an M-estimation problem, which leads to an unconstrained nonlinear optimization problem....

In this paper, the problems of state and fault estimation are addressed for a class of switched descriptor systems subject to Lipschitz nonlinearities and unknown inputs (UI). The UI appear both on the dynamic and on the measurement equations. Two problems are addressed by L2-gain minimization with the use of switched Lyapunov functions and formulated by LMI. First, a functional observer for sw...

A robust approach should be considered when estimating regression coefficients in multi-response problems. Many models are derived from the least squares method. Because the presence of outlier data is unavoidable in most real cases and because the least squares method is sensitive to these types of points, robust regression approaches appear to be a more reliable and suitable method for addres...

To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust (DDSE) method through off-line learning and on-line matching. At stage, linear regression equation is presented by clustering historical data from supervisory control acquisition (SCADA), which provides guarantee for solving over-learning problem existing DDSE methods; then novel that...

In autonomous applications for mobility and transport, a high-rate highly accurate vehicle-state estimation is achieved by fusing measurements of global navigation satellite systems (GNSS) inertial sensors. The state its protection-level generation often suffer from satellite-signal disturbances in urban environments subsequent poor parametrization the observables. Thus, we propose an innovativ...

State estimation in the energy management center of active distribution networks has attracted many attentions. Considering an increase in complexity and real-time management of active distribution networks and knowing the network information at each time instant are necessary. This article presents a two-step multi-area state estimation method in balanced active distribution networks. The prop...