In this paper, we describe a Continuously Adaptive Mean Shift (CAMshift) algorithm with a Kalman filter. A CAMshift algorithm does not consider an object’s direction vectors and velocity. In addition, sometimes, CAMshift loses the tracked object when the color of the background is similar to that of the object. However, using a Kalman filter with the CAMshift algorithm can overcome these disadv...

This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the sy...

This paper proposes an adaptive two-stage extended Kalman filter (ATEKF) for estimation of unknown fault bias in an INS-GPS loosely coupled system. The Kalman filtering technique requires complete specifications of both dynamical and statistical model parameters of the system. However, in a number of practical situations, these models may contain parameters, which may deviate from their nominal...

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. ...

Parameter estimation is considered to be one of the greatest challenges in computational systems biology. Biological experiments can measure only a fraction of the kinetic parameters and the rest has to be estimated in silico. Recently parameter estimation problems have been addressed in the framework of control theory. One of the most successful and widely used methods in control theory for es...

The present work proposes a control parameter adjustment technique using Kalman filter applied to an adaptive control strategy. The control algorithm is based on neural networks with on-line learning to compute the next action of the manipulated process variables. The penalization parameters of the control actions are on-line optimised by the Kalman filter. The control strategy was tested on an...