Dear Editor,This letter investigates the target enclosing control problem of multi-agent systems.A signed graph-based control strategy is presented,where the agents are steered to enclose the dynamic target from both ...
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Dear Editor,This letter investigates the target enclosing control problem of multi-agent systems.A signed graph-based control strategy is presented,where the agents are steered to enclose the dynamic target from both sides as they *** is inspired by the phenomenon that signed networks exhibit bipartite clustering if the underlying graph is structurally balanced,so that the agents may naturally enclose the zero point from opposite sides(+and.)if proper controllers are *** adopting a distributed observer to estimate the information of dynamic target。
The prediction of mixed gas consumption in hot rolling production is of great significance in gas production-consumption balance and energy saving. However, in the actual production process of hot rolling, the complex...
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This study addresses the problem of guaranteed cost fault-tolerant fuzzy control for multiline re-entrant manufacturing systems (RMSs) against stochastic disturbances and workstation faults. Initially, a nonlinear hyp...
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In this paper, a control method for shallow sleep management of low-power rockets is studied, and three sleep modes are verified for shallow sleep, and the optimal adaptation of shallow sleep of rockets with minimum p...
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Electromagnetic formation flight uses the electromagnetic interaction between satellites to provide control maneuvers for formation satellites, with the advantages of no propellant consumption, long life, and high fle...
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This paper proposes a multi-outlet internal rotating nozzle structure to address the issues of soot generation and friction/wear associated with mineral mining. The atomization and jet characteristics of the nozzle ar...
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In response to the situation where the first blade pick of a coal mining machine is prone to failure when cutting hard coal, the working process of the drum was simulated using finite element method. The force on the ...
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A reinforcement learning (RL) controller with identification of the dynamic parameter of hypersonic morphing flight vehicle (HMFV) is proposed in this paper, successfully realizing the end-to-end control of attack ang...
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Recent advances in satellite remote sensing technology and computer technology have significantly impacted practical applications in remote sensing image segmentation. However, the prevalent hybrid segmentation models...
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Recent advances in satellite remote sensing technology and computer technology have significantly impacted practical applications in remote sensing image segmentation. However, the prevalent hybrid segmentation models that combine Convolutional Neural Networks (CNNs) and Transformers, often overlook the critical exploration of local and global feature correlations across various scales. This exploration is essential for learning more representative features and strengthening context modeling capabilities. Additionally, the decoding layers of these models do not effectively exploit the pixel-level semantic relationships within cross-layer feature maps, thereby limiting the models' ability to discern small object features. To address these challenges, this paper introduces a Multi-directional and Multi-constraint Learning Network (MMLN) designed for semantic segmentation of remote sensing imagery. This network features a Multi-directional Dynamic Complement Decoder (MDCD), which enhances the interaction between local and global features in the feature space, and subsequently improves the feature discrimination within the segmentation network. Moreover, a Multi-constraint Saliency Boundary-adaptive Module (MSBM) is implemented to reinforce the spatial constraints on saliency at the edge regions and ensure semantic consistency along the mask boundaries. This, in turn, augments the segmentation model's capability to detect small objects. The evaluation on four datasets reveals that the MMLN outperforms the existing state-of-the-art methods in remote sensing imagery segmentation. The code is available at https://***/zhongyas/MMLN. Authors
This paper focuses on the performance of equalizer zero-determinant(ZD)strategies in discounted repeated Stackelberg asymmetric *** the leader-follower adversarial scenario,the strong Stackelberg equilibrium(SSE)deriv...
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This paper focuses on the performance of equalizer zero-determinant(ZD)strategies in discounted repeated Stackelberg asymmetric *** the leader-follower adversarial scenario,the strong Stackelberg equilibrium(SSE)deriving from the opponents’best response(BR),is technically the optimal strategy for the ***,computing an SSE strategy may be difficult since it needs to solve a mixed-integer program and has exponential complexity in the number of *** this end,the authors propose an equalizer ZD strategy,which can unilaterally restrict the opponent’s expected *** authors first study the existence of an equalizer ZD strategy with one-to-one situations,and analyze an upper bound of its performance with the baseline SSE *** the authors turn to multi-player models,where there exists one player adopting an equalizer ZD *** authors give bounds of the weighted sum of opponents’s utilities,and compare it with the SSE ***,the authors give simulations on unmanned aerial vehicles(UAVs)and the moving target defense(MTD)to verify the effectiveness of the proposed approach.
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