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This paper studies a dynamic state estimation problem for power systems, which can be seen as the quasi-static systems. The state vector of each subsystem (called node) in power networks is expressed by measurements. Based on a distributed maximum a posteriori (MAP) estimation technique, a fully distributed state estimation method is presented to update the local state at each time instant. Also,...
Classic Mean Shift tracking algorithm always suffers from large position errors, which may lead to the failure on tracking target in complex environment. To handle this problem, an improved Mean Shift tracking algorithm based on texture and color feature fusion is proposed. The histograms of improved Local Binary Patterns (LBP) texture and color features are calculated with the algorithm. Then, along...
MEMS gyro has many outstanding advantages like cheap, small, light, less power dissipation, and etc., but its low performance limits its wide application. Based on the self-developed CRG20 MEMS gyro test platform, we experimentally studied Allan variance technique to analysis five common noise of the MEMS gyro. Then AR (1) model is adopted based on time-series data to construct the state equation...
This paper is concerned with the distributed fusion estimation problem for linear system observed by multirate sensors in the environment of wireless sensor networks (WSNs). Rates of the sampling, estimation, transmission in the WSNs are different. The distributed fusion estimation is composed of two stages. At the first stage, every sensor in the WSNs collects measurements of its own to generate...
Due to the noise and uncertainty, it is necessary for time series big data to capture the key information with estimation methods. The Kalman filter with adaptive method by part of samples can give the high dimensional characteristics, reduce the computing cost and data uncertainty, but encounter the irregular estimation. The number of sample and the performance of the abstracted information have...
In this paper, we investigate the Multiple Model Adaptive Estimation (MMAE) and present a new filtering method based on MMAE algorithm. This method is applied to the SINS/CNS integrated navigation system under the motion of ballistic missile. In this proposed algorithm, we use improved Kalman filters rather than traditional Kalman filters, such as Extended Kalman Filter (EKF), Unscented Kalman Filter...
Focus on the uncalibrated visual servo, we established a filtering system based on Kalman Filter, and validated it by Matlab. Then we discussed the stability precondition of the control system with Kalman Filter in detail, and made a conclusion that if and only if the origin system is completely controllable and observable, the filtering system can converged to the expected position. Refer to the...
Cyber-physical systems (CPSs) have been gaining popularity with their high potential in widespread applications, and the security of CPSs becomes a rigorous problem. In this paper, an output track control (OTC) method is designed for discrete-time linear time-invariant Gaussian systems. The output tracking error is regarded as an additional state, Kalman filter-based incremental state observer and...
This paper deals with the distributed estimation problem in a relative sensing network. Each node is governed by a homogeneous dynamic model and has the measurements of relative states between itself and its neighbors. A subset of nodes in the network, called anchor nodes, can additionally have the measurements of their own absolute states. The relative sensing network is modeled by a bidirectional...
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