In recent visual tracking research,correlation filter(CF)based trackers become popular because of their high speed and considerable *** methods mainly work on the extension of features and the solution of the boundary...
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In recent visual tracking research,correlation filter(CF)based trackers become popular because of their high speed and considerable *** methods mainly work on the extension of features and the solution of the boundary effect to learn a better correlation ***,the related studies are *** exploring the potential of trackers in these two aspects,a novel adaptive padding correlation filter(APCF)with feature group fusion is proposed for robust visual tracking in this paper based on the popular context-aware tracking *** the tracker,three feature groups are fused by use of the weighted sum of the normalized response maps,to alleviate the risk of drift caused by the extreme change of single ***,to improve the adaptive ability of padding for the filter training of different object shapes,the best padding is selected from the preset pool according to tracking precision over the whole video,where tracking precision is predicted according to the prediction model trained by use of the sequence features of the first several *** sequence features include three traditional features and eight newly constructed *** experiments demonstrate that the proposed tracker is superior to most state-of-the-art correlation filter based trackers and has a stable improvement compared to the basic trackers.
In this paper, the problem of decentralized adaptive filtering for multi-agent systems with uncertain couplings is formulated and investigated. This problem is challenging due to the mutual dependency of state estimat...
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In this paper, the problem of decentralized adaptive filtering for multi-agent systems with uncertain couplings is formulated and investigated. This problem is challenging due to the mutual dependency of state estimation and coupling estimation. First, the problem is divided into four typical types based on the origin of coupling relations and linearity of the agent dynamics. Then models of the four types are given and the corresponding decentralized adaptive filtering algorithms are designed for the purpose of estimation of the unknown states and couplings which denotes the relations between agents and their neighbor agents in terms of states or outputs simultaneously,with preliminary stability analysis and discussions. For testing the effects of algorithm, with the so-called certainty-equivalence principle, control signals are designed based on the results of state estimation and coupling estimation got by the proposed decentralized adaptive filtering algorithms. Extensive simulations are conducted to verify the effectiveness of considered algorithms..
This paper considers the robust attitude control problem of re-entry vehicle in the presence of the parametric uncertainties and external *** on SDRE method,an optimal sliding surface is first obtained through the min...
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ISBN:
(纸本)9781479900305
This paper considers the robust attitude control problem of re-entry vehicle in the presence of the parametric uncertainties and external *** on SDRE method,an optimal sliding surface is first obtained through the minimization of a selected performance index ***,an adaptive sliding mode controller is designed to guarantee the reachability condition of the related optimal sliding *** switching gains are obtained on-line through an adaptation scheme,which eliminates the requirement of a priori knowledge of the upper bound on the lumped *** effectiveness of the proposed strategy is verified by both theoretical analysis and simulation results.
The control problem of spacecraft eigenaxis maneuver in the presence of parametric uncertainty and external disturbance is addressed in this paper. Modified Rodrigues parameters (MRPs) are utilized as the attitude p...
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ISBN:
(纸本)9781467355339
The control problem of spacecraft eigenaxis maneuver in the presence of parametric uncertainty and external disturbance is addressed in this paper. Modified Rodrigues parameters (MRPs) are utilized as the attitude parameters for the non-redundancy. An eigenaxis maneuver control law with feedback and feed-forward terms is presented for the nominal system. The transient response of close loop system can be adjusted according to an approximate second order system. To improve the robustness, integral sliding mode (ISM) technique is adopted to reject undesirable effects and track nominal trajectory. The resulting controller can perform the eigenaxis maneuver in the presence of parametric uncertainty and external disturbance while possess good system performance. The effectiveness of the proposed method is demonstrated by simulation results.
Autonomous vehicles have attracted considerable attention in the research community and industry due to their potential benefits to unmanned driving and assisted driving. This paper addresses the problem of designing ...
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ISBN:
(纸本)9781467355322
Autonomous vehicles have attracted considerable attention in the research community and industry due to their potential benefits to unmanned driving and assisted driving. This paper addresses the problem of designing lateral control law and the strategy of determining the giving speed for autonomous vehicles. An improved method of calculating lateral offset and angle error based on multiple look-ahead distances is proposed to reduce the impact of noise in reference path data on the lateral control system. Multiple fuzzy inference engines are used to design the steering controller and determine the given driving speed including forward and backward to deal with both simple and complex reference paths. Satisfactory simulation and experimental results have been obtained for different reference paths including a path with U-turn task in which backward driving is needed.
This study examines a multi-player pursuit-evasion game, more specifically, a three-player lifeline game in a planar environment, where a single evader is tasked with reaching a lifeline prior to capture. A decomposit...
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This study examines a multi-player pursuit-evasion game, more specifically, a three-player lifeline game in a planar environment, where a single evader is tasked with reaching a lifeline prior to capture. A decomposition method based on an explicit policy is proposed to address the game qualitatively from two main aspects:(1) the evader's position distribution to guarantee winning the game(i.e., the escape zone),which is based on the premise of knowing the pursuers' positions initially, and(2) evasion strategies in the escape zone. First, this study decomposes the three-player lifeline game into two two-player sub-games and obtains an analytic expression of the escape zone by constructing a barrier, which is an integration of the solutions of two sub-games. This study then explicitly partitions the escape zone into several regions and derives an evasion strategy for each region. In particular, this study provides a resultant force method for the evader to balance the active goal of reaching the lifeline and the passive goal of avoiding capture. Finally,some examples from a lifeline game involving more than one pursuer are used to verify the effectiveness and scalability of the evasion strategies.
This paper presents a new method based on the polytopic linear differential inclusion and the robust mixed H2/∞ filtering for the design of the nonlinear filter with non-Gaussian noises. The main goal is to solve the...
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ISBN:
(纸本)9781467355322
This paper presents a new method based on the polytopic linear differential inclusion and the robust mixed H2/∞ filtering for the design of the nonlinear filter with non-Gaussian noises. The main goal is to solve the problems of the complexity and large calculation number in the general nonlinear filter and the filtering design problem for systems with the non-Gaussian noises. The noises considered in the paper involve two different kinds of noises: white noises and energy bounded noises. Differing from the linearization in most nonlinear filters, the estimation error system for the nonlinear system is represented by an uncertain polytopic linear model, based on which, the rectification equations for the predicted errors are designed following the robust mixed H2/∞ filtering. The state estimates for the nonlinear system are given through updating the predictions by the rectified quantities, where, the state predicted quantities of the nonlinear system are gained by the prediction equation of the EKF. The evident advantage of the new filter is the filter coefficients of the rectification equation are constant, without the need to evaluate the Jacobian matrixes. As a result, the calculation number for the new filter is decreased much and the real-time performance of the new filter is much better than the EKF, though the accuracy is a little decline. Its effectiveness is demonstrated by using an example and the statistics result of the calculation number for the filters in the example.
The problem of solving discrete-Time Lyapunov equations (DTLEs) is investigated over multiagent network systems, where each agent has access to its local information and communicates with its neighbors. To obtain a so...
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Recent years have seen a rising interest in distributed optimization problems because of their widespread applications in power grids, multi-robot control, and regression *** the last few decades, many distributed alg...
Recent years have seen a rising interest in distributed optimization problems because of their widespread applications in power grids, multi-robot control, and regression *** the last few decades, many distributed algorithms have been developed for tackling distributed optimization problems. In these algorithms, agents over the network only have access to their own local functions and exchange information with their neighbors.
This paper investigates whether advanced neural network techniques can be applied to the detection and identification of typical targets in the context of land warfare. We collected 13 typical targets and built a dete...
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ISBN:
(纸本)9781509046584
This paper investigates whether advanced neural network techniques can be applied to the detection and identification of typical targets in the context of land warfare. We collected 13 typical targets and built a detection data set. Based on the Faster R-CNN framework, we improve the detection accuracy by two ways. First, we design a neural network model with strong local modeling capabilities. Second, we combine middle layers and the last layer of feature maps as the detection features to enhance the detection ability and improve the detection accuracy.
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