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In this paper, a new mathematical model is built according to the characteristics of the BLDC motor and a new filtering algorithm is proposed for sensorless brushless DC (BLDC) motor based on Unscented Kalman Filter(UKF). The proposed UKF algorithm is employed to estimate the speed and rotor position of the BLDC motor only using the measurements of terminal voltages and three-phase currents. In order...
This paper investigates the multi-sensor information fusion estimation problem for sensor networks with nonuniform sampling rates. The measurements are sampled asynchronously by the various sensors with nonuniform sampling rates. Then, each sensor in the network acts also as an estimator and collects measurements from its neighbors to generate estimates by applying a distributed measurement fusion...
This paper introduces a method to control a two-wheeled self-balancing robot based on Kalman filter and LQR algorithm. It is incorporated with hardware design, signal processing and control algorithm design. In this system the angle signals from a gyroscope and an accelerometer, disposed by Kalman filter, are combined with LQR controller to accomplish the controlling of the robot. The purpose of simplifying...
In the vision measurement of high-speed moving target, the system should with high data-update rate and maintain it stable. Cooperative markers also should be correctly matched. As the markers on the moving target with large displacement in the images between frames, the conventional neighborhood search method with a fixed neighborhood size would decrease the system data-update rate, mismatch the...
A new approach to sensorless speed estimation is derived in the unbiased minimum variance sense by applying the Unknown Input Kalman Filter (UIKF) in the networked environment. The recursive Networked Unknown Sensor Input Extend Kalman Filter (NUSIEKF) is developed to deal with the sensorless speed estimation problem for permanent magnet synchronous motor (PMSM) in the existence of packet dropout...
In this paper, we devote to investigating the consensus-based unscented Kalman filtering problem for a certain kind of sensor networks with sensor saturations. The communication status among sensors is represented by a connected undirect graph. Saturation phenomenon exists both in the state of the system and individual sensors. Moreover, a distributed unscented Kalman filtering algorithm based on...
This paper develops a new adaptive unscented Kalman filter based on covariance-matching technique for nonlinear system with unknown statistical characteristics of the noises. The variances of process noise and measurement noise can be estimated online simultaneously by using information of innovation and residual sequence, and the accuracy of UKF will be improved. Furthermore, we show that the statistical...
This paper is to study the linear minimum variance estimation for discrete-time singular WSN systems with multiplicative noises and additive noises. The state and the state disturbed by multiplicative noise are both included in the observation equation. A simple approach of projection theorem is proposed.
A measurement system based on dynamic target tracking with laser-electronic theodolites is represented in order to realize automatic spatial measurement for moving targets in large scale. The structure of the measurement system which consists of external scanning equipment and laser-electronic theodolite is proposed. The measurement model of the video camera is established by coordinate system transformation...
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