A main problem encountered in control engineering is the estimation of unknown parameters appearing in the plant equations. In this paper, a new off-line method to perform such estimation is proposed. The method is based on the use of the plant simulator and on the generation of artificial data from which the relationship between the unknown parameter vector and available measurements is estima...

The problem of localization is well known in mobile robotics. A solution is to use a model-based technique such as a kalman filter with multi sensor data fusion. For a car-like mobile robot, the nonlinear dynamic model is suitable for robot movement representation. This work presents the discrete extended kalman filter including a nonlinear dynamic model for the mobile robot localization. As in...

The Kalman filtering method is extended to two dimensions. The resulting computational load is found to be excessive. Two new approximations are then introduced. One, called the strip processor, updates a line segment at a time; the other, called the reduced update Kalman filter, is a scalar processor. The reduced update Kalman filter is shown to be optimum in that it minimizes the post update ...

Satellite autonomous orbit determination OD is a complex process using filtering method to integrate observation and orbit dynamic equations effectively and estimate the position and velocity of a satellite. Therefore, the filtering method plays an important role in autonomous orbit determination accuracy and time consumption. Extended Kalman filter EKF , unscented Kalman filter UKF , and unsce...