Smooth Variable Structure Filter VSLAM

The Continuous-time Smooth Variable Structure Filter

State and parameter estimation techniques are important tools which provide accurate estimates of system states. This is important for the reliable and safe control of mechanical and electrical systems. Most estimation techniques are derived in discrete-time, due to the wide use of digital computers. However, continuous-time derivations do exist, and are particularly useful for studying estimat...

The Smooth Particle Variable Structure Filter

In this paper, a new state and parameter estimation method is introduced based on the particle filter (PF) and the smooth variable structure filter (SVSF). The PF is a popular estimation method, which makes use of distributed point masses to form an approximation of the probability distribution function (PDF). The SVSF is a relatively new estimation strategy based on sliding mode concepts, form...

Neural Networks and the Smooth Variable Structure Filter

Robust Visual Simultaneous Localization and Mapping for MAV Using Smooth Variable Structure Filter

The work presented in this paper is a part of research work on autonomous navigation for Micro Aerial Vehicles (MAVs). Simultaneous Localization and Mapping (SLAM) is crucial for any task of MAV navigation. The limited payload of the MAV makes the single camera as best solution for SLAM problem. In this paper the Large Scale Dense SLAM (LSD-SLAM) pose is fused with inertial data using Smooth Va...

Mitigation of Switching Harmonics in Shunt Active Power Filter Based on Variable Structure Control Approach

This paper presents a novel control approach used in shunt active power filter based on variable structure control combined with Random PWM technique (RVSC) that provides robust, fast, and more favorable performance for active power filter. This control strategy is compared with two other strategies to show the effectiveness of the introduced methods; pulse width modulated proportional-integral...