This paper will conduct an exhaustive analysis of sliding mode and variable structure filters,
essential methodologies employed in signal processing that solve problems noisy and …

The sliding innovation filter (SIF) is a newly developed filter that shares similar principles
with sliding mode observers and variable structure techniques. The SIF is formulated as a …

The sliding innovation filter (SIF) is a state and parameter estimation strategy based on
sliding mode concepts. It has seen significant development and research activity in recent …

This paper proposes a novel sliding mode filter, which improves Emaru et al.'s filter.
Compared to previous filters, the proposed filter has a faster response speed without …

The smooth variable structure filter (SVSF) is a relatively new state and parameter estimation
technique. Introduced in 2007, it is based on the sliding mode concept, and is formulated in …

The smooth variable structure filter (SVSF) has seen significant development and research
activity in recent years. It is based on sliding mode concepts, which utilizes a switching gain …

The Kalman filter (KF) remains the most popular method for linear state and parameter
estimation. Various forms of the KF have been created to handle nonlinear estimation …

The smooth variable structure filter (SVSF) is a type of sliding mode filter formulated in a
predictor-corrector format and has seen significant development over the last 15 years. In …

The paper introduces the concept of a filtering controller (FC), which uses sliding mode
control as its basis. The FC 'seamlessly'integrates a smoothed variable structure filter with a …

The sliding innovation filter (SIF) is a newly developed filter that may be applied to both
linear and non-linear systems. The SIF shares similar principles with sliding mode observers …