This paper compares two sensorial fusion algorithms based on their characteristics and
performance when applied to a localization system for an autonomous wheelchair in …

This chapter deals with optimal state estimation for dynamic systems. The Bayesian
methodology provides a general framework for this problem. An example of recent interest is …

State space estimation approaches are one of the finest approaches to predict the future
behavior of real time systems like tracking, navigation, guidance systems etc. Kalman filter is …

Monitoring of mechatronic systems is one of the essential issues in the industries. In this
context, we firstly deal with the modeling of an electro-mechanical system obtained by …

Lithium-ion batteries are in the top priority among other batteries because of being safe,
quick charging, and long-life cycle and are widely used in electric vehicles for having …

Rényi entropy as a generalization of the Shannon entropy allows for different averaging of
probabilities of a control parameter α. This paper gives a new perspective of the Kalman …

To know the characteristics of a system, it is important to estimate the state of the system.
State estimation can be done using stochastic estimators. Kalman filter is one of the linear …

Estimating un-measurable states is an important component for onboard diagnostics (OBD)
and control strategy development in diesel exhaust aftertreatment systems. This paper …

Lithium-ion batteries are preferred more than other types of batteries in electric vehicle
applications due to their inherent safety, fast charge capacity, and long life. To create an …

Bio-inspired robotics engineers look to the natural world for clues to aspects of motion
dynamics and morphologies that may be incorporated in the design of these robots. The …