In this paper, distributed containment control problems of general linear multi-agent systems are investigated. The objective is to make the followers in a multi-agent network converge to the convex hull spanned by so...
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In this paper, distributed containment control problems of general linear multi-agent systems are investigated. The objective is to make the followers in a multi-agent network converge to the convex hull spanned by some leaders whose control inputs are nonzero and not available to any *** mode surfaces are defined for the cases of reduced order and non-reduced order, respectively. For each case, fast sliding mode controllers are designed. It is shown that all the error trajectories exponentially reach the sliding mode surfaces in a finite time if for each follower, there exists at least one of the leaders who has a directed path to the follower, and the leaderscontrol inputs are bounded. The control Lyapunov function for exponential finite time stability, motivated by the fast terminal sliding mode control, is used to prove reachability of the sliding mode surfaces. Simulation examples are given to illustrate the theoretical results.
Existing causal inference methods for social media usually rely on limited explicit causal context, preassume certain user interaction model, or neglect the nonlinear nature of social interaction, which could lead to ...
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Existing causal inference methods for social media usually rely on limited explicit causal context, preassume certain user interaction model, or neglect the nonlinear nature of social interaction, which could lead to bias estimations of causality. Besides, they often require sufficiently long time series to achieve reasonable results. Here we propose to take advantage of multivariate embedding to perform causality detection in social media. Experimental results show the efficacy of the proposed approach in causality detection and user behavior prediction in social media.
Revealing underlying social influence among users in social media is critical to understanding how users interact, on which a lot of security intelligence applications can be built. Existing methods fail to take into ...
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Revealing underlying social influence among users in social media is critical to understanding how users interact, on which a lot of security intelligence applications can be built. Existing methods fail to take into account the interaction relationships among memes. In this paper, we propose to simultaneously model social influence and meme interaction in information diffusion with novel multidimensional Hawkes processes. Experimental results on both synthetic and real world social media data show the efficacy of the proposed approach.
In this paper, a new single sample face recognition approach based on lower-upper (LU) decomposition is proposed. The single sample and its transpose are decomposed to two sets of basis images respectively by LU decom...
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ISBN:
(纸本)9781479978632
In this paper, a new single sample face recognition approach based on lower-upper (LU) decomposition is proposed. The single sample and its transpose are decomposed to two sets of basis images respectively by LU decomposition algorithm. Two approximation images are reconstructed from the two basis image sets respectively by the experimental estimation method. The fisher linear discriminant analysis (FLDA) is used to evaluate the optimal projection space using the new training set consisting of the single sample and its two approximation images for each person. We make two main contributions: one is that we propose to decompose the single sample and its transpose using the efficient LU decomposition algorithm; the other is that we present an experimental estimation method using the fixed image size to evaluate the number of basis images, which are used to reconstruct the approximation image. The experimental results on the FERET and AR face databases indicate that the proposed method is efficient and outperforms several state-of-the-art approaches which are proposed to address the single sample per person problem.
Hydro-viscous speed clutch(HVC) is a central control element of the driver system. Because of nonlinearities and hysteresis of the clutch, the setting of control parameters has a significant impact on the performance ...
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Hydro-viscous speed clutch(HVC) is a central control element of the driver system. Because of nonlinearities and hysteresis of the clutch, the setting of control parameters has a significant impact on the performance of the speed control system. This paper studies the HVC of a vehicle temperature control system, and analyzes the parameters tuning method of a PID controller for the closed-loop control system. By employing a two-storey optimized control framework, the resulting model from identification can be used to complete the control parameters auto-tuning. Simulation and experimental results have showed that this auto-tuning method can obtain a group of parameters in terms of a desired performance index, which guarantees the balance of dynamic characteristics, stability and anti-jamming in closed-loop system.
This paper presented a hierarchical fuzzy path following control scheme based on different fuzzy grain size in a class of unknown environment with static *** employing fine-grained fuzzy division and design of fuzzy r...
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This paper presented a hierarchical fuzzy path following control scheme based on different fuzzy grain size in a class of unknown environment with static *** employing fine-grained fuzzy division and design of fuzzy rule table for the rotation angle and speed of a robot,a more accurate path following control was achieved,while more effective fuzzy obstacle avoidance was realized with coarse-grained fuzzy division *** proposed controller was a two-leveled architecture in which the higher level was the decision-making of the sub-task switching of path following or obstacle avoidance,while the lower level was motion control of path following and fuzzy obstacle ***,the simulation experiments were carried out to demonstrate the feasibility and effectiveness of the proposed scheme.
This paper considers the consensus problem synthesized with transient performance for a class of linear systems subject to input saturation. Two different settings, the undirected communication topology and a directed...
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ISBN:
(纸本)9781509002443
This paper considers the consensus problem synthesized with transient performance for a class of linear systems subject to input saturation. Two different settings, the undirected communication topology and a directed communication topologies, are systematically considered. To improve the transient performance of the resulting consensus, a saturated nonlinear consensus algorithm is proposed to solve this problem. Consensus tracking control for a class of linear systems is proved to be achieved under the general undirected and a directed graphs provided that their generated graphs contain a directed spanning tree. Numerical examples are utilized to illustrate the effectiveness of the theoretical results.
In this paper,an iterative adaptive dynamic programming(ADP) algorithm is developed to solve the optimal cooperative control problems for residential multi-battery *** avoid solving high-dimensional optimal control pr...
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In this paper,an iterative adaptive dynamic programming(ADP) algorithm is developed to solve the optimal cooperative control problems for residential multi-battery *** avoid solving high-dimensional optimal control problems,we first constrain all the batteries at their worst performance,which transforms the multi-input optimal control problem into a single-input *** on the worst-performance optimal control law,the optimal cooperative control law for the residential multi-battery systems is obtained,where in each iteration,only a single-input optimization problem is ***,numerical results are given to illustrate the performance of the developed algorithm.
We experience changes in stationarity/time variance in many practical applications. Since changes modify the operational framework the application is working with, its accuracy performance is in turn affected. When ch...
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ISBN:
(纸本)9781479975617
We experience changes in stationarity/time variance in many practical applications. Since changes modify the operational framework the application is working with, its accuracy performance is in turn affected. When changes can occur, we need to detect them as soon as possible, in general by inspecting features extracted from data, and afterwards intervene to mitigate their effects. In this paper, we propose a novel change detection test based on the least squares density difference estimation. Neither assumptions about the distribution of features are needed, nor the change types are made (the method is pdf-free and can handle arbitrary changes.). What here proposed requires limited data to become operational and thresholds needed to assess the change can be set met to predefined false positive rates. We show through comprehensive experiments the effectiveness of the detection method and point out how it outperforms other related methods.
For the dynamic obstacle avoidance problem in a unknown environment,a second-order fuzzy control strategy is proposed based on fuzzy *** the observation and analysis of the perception information of the delta speed an...
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ISBN:
(纸本)9781479970186
For the dynamic obstacle avoidance problem in a unknown environment,a second-order fuzzy control strategy is proposed based on fuzzy *** the observation and analysis of the perception information of the delta speed and the delta deviation angle of a detected dynamic obstacle,the robot then make decision to efficiently avoid dynamical ***,a two hierarchical control scheme is designed,where the upper level is to determine the deflection angle according to delta of speed and direction of dynamic obstacles,and the lower one is to derive the speed of a robot by employing the output of the upper level and the distance between the robot and dynamic *** simulations are demonstrated that the proposed scheme is effective and efficient.
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