Papers by Keyword: Kalman Filter (KF)

Abstract: This paper brings out a new sparse line-optical flow field computing method. Firstly, we establish a lines matching algorithm based on Kalman Filter (KF). In this algorithm, we map lines in an image into Hough space, after that we employ KF to predict the position in the following frame in order to match lines in image sequence. Secondly, we present the concept of sparse line-optical flow field of images and propose the calculation method of it. By using the camera perspective projection model and the optical flow Identity, we can get the sparse line-optical flow field. Simulations is made in the following step, and results show that the lines matching algorithm works well and the accuracy of the calculation method proposed in this paper is as good as that of the classic Horn algorithm, while the calculating time-cost of it is only 1/30 Horn algorithms.

Abstract: In this paper,information technology is introduced briefly and in order to avoid inaccurate segmentation of moving objects caused by object holes and ghost, an automatic moving object segmentation method which belongs to information technology based on memory matrix and Kalman filter theory is proposed. Memory matrix is used in multiple channels to extract the initial background, and ghost is eliminated after updating background according to the theory of Kalman filter. Moving objects are extracted using adaptive threshold, and object segmentation is achieved by improved region growing method on base of block processing. The experimental results indicate that the proposed algorithm can accurately segment moving object from video sequences, and has very good robustness against illumination variance and moving noise.

Abstract: For the passive and semi-active suspensions are characterized as with constant parameters which cannot cope with time-variant road conditions, the suspension results are difficult to be satisfied. Although, the active ones are better than previous two on suspension performance, until now which are still far from real application for the drawbacks of complicated structure, large volume, costly, and difficult maintenance. Here, Ball Screw (BS) is with the characteristics of smaller volume, precise positioning, and well handling high-speed forward and backward transmissions. Instead of hydraulic or pneumatic mechanisms used for vehicle suspension, BS is adopted to be the main body of the proposed New Adaptive Suspension System (NASS). Besides, in order to overcome the unavoidable time-delay resulted from mechanical or computational operations, the Kalman filter, integrated with suspension controller, is used to estimate the road conditions. The effectiveness and feasibility of this proposal are confirmed through simulation studies.

Abstract: This article investigates how the scale and structure of energy production influence on sustainable economic development in China. First and foremost, the relationship between energy production and economic development was discussed in theory, and a time-varying parameter state space model was established. Then an empirical study based on the annual data from 1981 to 2012 was carried out by using method of Kalman filter. The results indicate that both the increasing scale of energy production and the increasing proportion of new energy have a positive and significant influence on Chinese economic growth. Finally, the thesis draws a conclusion that, expanding the scale of energy production and optimizing the structure of energy production will significantly promote China's sustainable economic growth.

Abstract: The noise signal caused by measurement and observation seriously affected the control quality in PID control of DC motor. A PID regulation technology was proposed which was based on Kalman filter. The system state was estimated by the Kalman filter so that the measurement and observation noise signal was inhibited thus resulting in the system performance improved. The designed controller was dynamically simulated in MATLAB. The results showed that the noise signal existed in the system was effectively filtered by PID regulation technology with Kalman filter so that the system performance was improved.

Abstract: In order to improve the dynamic response, the steady state precision and the anti-disturbance capability of the brushless DC motor drive system, a kind of adaptive compensation control strategy combining with the linear quadratic optimal control and fuzzy control theory is proposed in this paper. According to the state space model of Brushless DC motor, the Kalman filter is adopted to estimate the state variables. The optimal state feedback control matrix is given by linear quadratic optimal control theory. The deviation caused by random disturbance is compensated by the output of fuzzy controller. The results of simulation show that proposed method can not only effectively suppress random disturbance, but also has good speed regulation performance.

Abstract: For multisensor network systems with unknown cross-covariances, a novel multi-level parallel covariance intersection (PCI) fusion Kalman filter is presented in this paper, which is realized by the multi-level parallel two-sensor covariance intersection (CI) fusers, so it only requires to solve the optimization problems of several one-dimensional nonlinear cost functions in parallel with loss computation burden. It can significantly reduce the computation time and increase data processing rate when the number of sensors is very large. It is proved that the PCI fuser is consistent, and its accuracy is higher than that of each local filter and is lower than that of the optimal Kalman fuser weighted by matrices. The geometric interpretation of accuracy relations based on the covariance ellipses is given. A simulation example for tracking systems verifies the accuracy relations.

Abstract: Based on the standard Kalman filter, considering the actual problems of the sonar altimeter is susceptible to the environment and its accuracy is poor, put forward a kind of adaptive algorithm based on n iterations to adjust observation noise. By adjusting the observation noise covariance, to make it more close to the actual value, so as to improve the accuracy of the altimeter data. Experiment show that the algorithm is effective.

Abstract: This paper focused on the dynamic Jcobian identification for robot visual feedback control in unstructured environments, there is the robotic manipulator without kinematics model, and the camera without calibration. First, a visual servoing scheme based on Kalman filtering (KF) to model-independent robotic manipulation is proposed. The Jacobian identification were solved by formatted as state estimation problems, the desired Jacobian is optimal estimated under minimum-variance condition to achieves robotic precise converge to the desired pose. Our method, without requiring modeling parameters, thus this avoids the corrupted performances cause by calibration errors. To demonstrate the performance of proposed scheme, the experimental results have been presented using eye-in-hand configurations.

Abstract: The recent decades have witnessed active studies in fault detection and isolation (FDD) of the small satellites subject to actuator failures and attitude coordination control of spacecraft formation flying (SFF) which plays a significant role in missions such as synthetic-aperture radar imaging. However, because of the time delay in communication links, the performance of coordination control is not always satisfactory. In this paper we propose a method to estimate the actuator fault as well as the input time delay at the same time. First of all, the model of the altitude control system of the small satellite with actuator fault and the model of the altitude control system with actuator fault and the input time delay are presented respectively. Based on the Two-Stage Kalman Filter algorithm, the fault and input time delay of the altitude control system of the small satellite can be estimated. At last, the simulation of the algorithm in a satellite attitude control system with actuator fault and input time delay will illustrate the effectiveness of the proposed approach.