Inverse synthetic aperture radar (ISAR) imaging based on compressed sensing (CS) theory can recover complete information from limited ISAR echo signals and reduce the imaging cost of ISAR. The traditional Smooth L0 no...
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Aiming at the cooperative search problem in a wide-area unknown region, a cooperative search strategy of multi-UAVs based on hexagonal grid is proposed for the fairness of decision-making, This strategy is trained by ...
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2D human pose estimation (HPE) has been a research focus of computer vision, 2D HPE baseline is one of the main *** the field of HPE continues to evolve, Vision Transformer Baselines have emerged as a significant area...
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Network localization serves as a fundamental component for enabling various position based operations in multi-agent systems,facilitating tasks like target searching and formation control by providing accurate positio...
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Network localization serves as a fundamental component for enabling various position based operations in multi-agent systems,facilitating tasks like target searching and formation control by providing accurate position information for all nodes in the *** localization focuses on the challenge of determining the positions of nodes within a network,relying on the known positions of anchor nodes and internode relative *** the past few decades,distributed network localization has garnered significant attention from *** paper aims to provide a review of main results and advancements in the field of distributed network localization,with a particular focus on the perspective of graph *** to its favorable characteristics,graph Laplacian unifies various network localization,even when dealing with diverse types of internode relative measurements,into a unified protocol framework,which can be constructed by a linear method and ensure the global convergence.
This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the sl...
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This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation *** the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost *** the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement *** combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop *** proposed decomposition design not only bypasses the numerical stiffness but also alleviates the *** efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.
Unmanned clusters can realize collaborative work,fexible confguration,and efcient operation,which has become an important development trend of unmanned *** positioning is important for ensuring the normal operation of...
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Unmanned clusters can realize collaborative work,fexible confguration,and efcient operation,which has become an important development trend of unmanned *** positioning is important for ensuring the normal operation of unmanned *** existing solutions have some problems such as requiring external system assistance,high system complexity,poor architecture scalability,and accumulation of positioning errors over *** the aid of the information outside the cluster,we plan to construct the relative position relationship with north alignment to adopt formation control and achieve robust cluster relative *** on the idea of bionics,this paper proposes a cluster robust hierarchical positioning architecture by analyzing the autonomous behavior of pigeon *** divide the clusters into follower clusters,core clusters,and leader nodes,which can realize fexible networking and cluster *** at the core cluster that is the most critical to relative positioning in the architecture,we propose a cluster relative positioning algorithm based on spatiotemporal correlation *** the design idea of low cost and large-scale application,the algorithm uses intra-cluster ranging and the inertial navigation motion vector to construct the positioning equation and solves it through the Multidimensional Scaling(MDS)and Multiple Objective Particle Swarm Optimization(MOPSO)*** cluster formation is abstracted as a mixed direction-distance graph and the graph rigidity theory is used to analyze localizability conditions of the *** designed the cluster positioning simulation software and conducted localizability tests and positioning accuracy tests in diferent *** with the relative positioning algorithm based on Extended Kalman Filter(EKF),the algorithm proposed in this paper has more relaxed positioning conditions and can adapt to a variety of *** also has higher relative positioning accuracy
Short-term residential load forecasting is essential to demand side response. However, the frequent spikes in the load and the volatile daily load patterns make it difficult to accurately forecast the load. To deal wi...
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In this paper,the distributed Nash equilibrium seeking problem of aggregative games,with players been presented by uncertain nonlinear systems over directed graphs,is *** problem aims at designing a distributed algori...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In this paper,the distributed Nash equilibrium seeking problem of aggregative games,with players been presented by uncertain nonlinear systems over directed graphs,is *** problem aims at designing a distributed algorithm for each player such that the player's state is bounded,while the player's output converges to the Nash equilibrium point.A dynamic compensator is firstly proposed by utilizing gradient-based protocol and average consensus *** the distributed Nash equilibrium seeking problem is converted into a tracking ***,the resulting tracking problem is addressed by developing a novel output feedback *** is shown that the concerned distributed Nash equilibrium seeking problem can be solved by the distributed algorithm composed of the dynamic compensator and the output feedback controller.
This paper addresses a distributed dynamic state estimation problem in large-scale systems characterized by a cyclic network graph. The objective is to develop a distributed estimation algorithm for each node to gener...
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This paper addresses a distributed dynamic state estimation problem in large-scale systems characterized by a cyclic network graph. The objective is to develop a distributed estimation algorithm for each node to generate local state estimations, based on the coupled measurements and boundary information exchanged with neighboring nodes. Our proposed approach is grounded in the maximum a posteriori(MAP)estimation method, which yields suboptimal results in acyclic network graphs compared with the centralized MAP approach. We extend this approach to systems with a cyclic network graph. Furthermore, we provide an accuracy analysis by deriving bounds for the differences in estimation error covariance and state estimation between the proposed distributed algorithm and the suboptimal centralized MAP method. These bounds apply to a specific category of systems that satisfy certain conditions, including cyclic topology and sparse connections. We demonstrate that these bounds converge asymptotically, with the rate of convergence determined by the loop-free depth of the graph. The loop-free depth of the graph refers to the maximum number of nodes that can be traversed in a cycle without revisiting any node. Finally, we demonstrate the validity of the algorithm through numerical examples.
Fly-around is important in many tasks such as on-orbit servicing. When a target exhibits game-playing behavior such as orbit maneuver for evasion, predesigned fly-around formation and control strategies can't deal...
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