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1.
IEEE Trans Cybern ; 54(8): 4617-4629, 2024 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-38261506

RESUMEN

This study focuses on distributed event-triggered consensus control under the scenario where only inaccurate agent model information is available. By designing a novel triggering error, a distributed dynamic event-triggered consensus (DETC) protocol is proposed for multiagent systems (MASs) with general linear dynamics over digraphs, without accurate a priori information of agent models. To improve the efficiency of the dynamic triggering law, a mixed triggering threshold is designed with a resilient function integrated to further enlarge interevent intervals. Within the proposed DETC protocol, the computational cost is significantly reduced especially for MASs with nonsparse and high-dimensional agent system matrices. In addition, for each individual agent, the states of neighboring agents used for triggering detections or controller updates are required in an on-demand (instead of continuous) way, which preserves communication resources and facilitates practical implementation. The feasibility of the designed DETC protocol is corroborated by rigorous theoretical analysis on consensus convergence and Zeno behavior exclusion. Finally, simulations are shown to demonstrate the effectiveness of the studied theory.

2.
Sensors (Basel) ; 23(17)2023 Aug 30.
Artículo en Inglés | MEDLINE | ID: mdl-37687974

RESUMEN

Visual object tracking is a fundamental task in computer vision that requires estimating the position and scale of a target object in a video sequence. However, scale variation is a difficult challenge that affects the performance and robustness of many trackers, especially those based on the discriminative correlation filter (DCF). Existing scale estimation methods based on multi-scale features are computationally expensive and degrade the real-time performance of the DCF-based tracker, especially in scenarios with restricted computing power. In this paper, we propose a practical and efficient solution that can handle scale changes without using multi-scale features and can be combined with any DCF-based tracker as a plug-in module. We use color name (CN) features and a salient feature to reduce the target appearance model's dimensionality. We then estimate the target scale based on a Gaussian distribution model and introduce global and local scale consistency assumptions to restore the target's scale. We fuse the tracking results with the DCF-based tracker to obtain the new position and scale of the target. We evaluate our method on the benchmark dataset Temple Color 128 and compare it with some popular trackers. Our method achieves competitive accuracy and robustness while significantly reducing the computational cost.

3.
Cyborg Bionic Syst ; 4: 0050, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-37649682

RESUMEN

Visual tracking is a crucial skill for bionic robots to perceive the environment and control their movement. However, visual tracking is challenging when the target undergoes nonrigid deformation because of the perspective change from the camera mounted on the robot. In this paper, a real-time and scale-adaptive visual tracking method based on best buddies similarity (BBS) is presented, which is a state-of-the-art template matching method that can handle nonrigid deformation. The proposed method improves the original BBS in 4 aspects: (a) The caching scheme is optimized to reduce the computational overhead, (b) the effect of cluttered backgrounds on BBS is theoretically analyzed and a patch-based texture is introduced to enhance the robustness and accuracy, (c) the batch gradient descent algorithm is used to further speed up the method, and (d) a resample strategy is applied to enable the BBS to track the target in scale space. The proposed method on challenging real-world datasets is evaluated and its promising performance is demonstrated.

4.
ISA Trans ; 129(Pt B): 243-256, 2022 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-35248367

RESUMEN

This paper investigates the problem of fixed-time attitude coordinated control for multi-spacecraft systems with unknown external disturbance. Firstly, a distributed fixed-time observer is introduced to estimate the states of the virtual leader. The observer can track the leader completely in a fixed time without dependence on the initial conditions of the leader and observer. Then, we propose a novel nonsingular fixed-time sliding mode tracking controller to address the fixed-time attitude tracking problem. It is noteworthy that the requirement on initial conditions of spacecraft is removed in the proposed nonsingular sliding mode controller. Due to the robustness of sliding mode control, the influence of external disturbance can be eliminated, such that each spacecraft can track desired attitude trajectories precisely in a fixed time. Hence, the fixed-time attitude coordination for multiple spacecraft can be achieved. Finally, numerical simulation results and comparisons reveal the effectiveness of the proposed algorithms.

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