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A Review on Extended Kalman Filtering Approach to Nonlinear Time Delay Systems


Author(s):

Aruj Kumar Verma , SHRI SHANKRACHARYA TECHNICAL CAMPUS, BHILAI; Rakesh Mandal, SHRI SHANKRACHARYA TECHNICAL CAMPUS, BHILAI; Khemlal Sinha, SHRI SHANKRACHARYA TECHNICAL CAMPUS, BHILAI

Keywords:

Kalman Filter (KF), Extended Kalman filter (EKF), nonlinear time-delay systems, Real-time systems

Abstract:

The Kalman Filter are used to estimates system states from the sequential noise measurements of the outputs. Another hand, real time system is often modeled with uncertainties and time-delay. Developing Kalman filter (KF) algorithms for this type of systems are an important problem to obtain optimal state estimated by the utilizing the information on uncertainty and time-delays. First designing of KF for nominal discrete-time systems are studied. Considering the co-variance error in the estimation of the KF algorithms are derived which is further tested on a numerical example. Next, development of KF for nonlinear time delay systems are considered. Similar to the previous design, considering covariance of estimation of the error, an Extended Kalman Filter (EKF) are developed based on the structure and normal information of the plant and The performance of the designed EKF are also compared with that of the KF designed for the same type of nominal system. It’s observed that the performance of the RKF are better than the KF.


Other Details:

Manuscript Id :IJSTEV3I11081
Published in :Volume : 3, Issue : 11
Publication Date: 01/06/2017
Page(s): 147-150
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