82 research outputs found
Accelerated K-Serial Stable Coalition for Dynamic Capture and Resource Defense
Coalition is an important mean of multi-robot systems to collaborate on
common tasks. An effective and adaptive coalition strategy is essential for the
online performance in dynamic and unknown environments. In this work, the
problem of territory defense by large-scale heterogeneous robotic teams is
considered. The tasks include exploration, capture of dynamic targets, and
perimeter defense over valuable resources. Since each robot can choose among
many tasks, it remains a challenging problem to coordinate jointly these robots
such that the overall utility is maximized. This work proposes a generic
coalition strategy called K-serial stable coalition algorithm (KS-COAL).
Different from centralized approaches, it is distributed and complete, meaning
that only local communication is required and a K-serial Stable solution is
ensured. Furthermore, to accelerate adaptation to dynamic targets and resource
distribution that are only perceived online, a heterogeneous graph attention
network (HGAN)-based heuristic is learned to select more appropriate parameters
and promising initial solutions during local optimization. Compared with manual
heuristics or end-to-end predictors, it is shown to both improve online
adaptability and retain the quality guarantee. The proposed methods are
validated rigorously via large-scale simulations with 170 robots and hardware
experiments of 13 robots, against several strong baselines including GreedyNE
and FastMaxSum.Comment: 8 pages, 10 figures, 1 tabl
Confucius Queue Management: Be Fair But Not Too Fast
When many users and unique applications share a congested edge link (e.g., a
home network), everyone wants their own application to continue to perform well
despite contention over network resources. Traditionally, network engineers
have focused on fairness as the key objective to ensure that competing
applications are equitably and led by the switch, and hence have deployed fair
queueing mechanisms. However, for many network workloads today, strict fairness
is directly at odds with equitable application performance. Real-time streaming
applications, such as videoconferencing, suffer the most when network
performance is volatile (with delay spikes or sudden and dramatic drops in
throughput). Unfortunately, "fair" queueing mechanisms lead to extremely
volatile network behavior in the presence of bursty and multi-flow applications
such as Web traffic. When a sudden burst of new data arrives, fair queueing
algorithms rapidly shift resources away from incumbent flows, leading to severe
stalls in real-time applications. In this paper, we present Confucius, the
first practical queue management scheme to effectively balance fairness against
volatility, providing performance outcomes that benefit all applications
sharing the contended link. Confucius outperforms realistic queueing schemes by
protecting the real-time streaming flows from stalls in competing with more
than 95% of websites. Importantly, Confucius does not assume the collaboration
of end-hosts, nor does it require manual parameter tuning to achieve good
performance
Output Voltage Response Improvement and Ripple Reduction Control for Input-parallel Output-parallel High-Power DC Supply
A three-phase isolated AC-DC-DC power supply is widely used in the industrial
field due to its attractive features such as high-power density, modularity for
easy expansion and electrical isolation. In high-power application scenarios,
it can be realized by multiple AC-DC-DC modules with Input-Parallel
Output-Parallel (IPOP) mode. However, it has the problems of slow output
voltage response and large ripple in some special applications, such as
electrophoresis and electroplating. This paper investigates an improved
Adaptive Linear Active Disturbance Rejection Control (A-LADRC) with flexible
adjustment capability of the bandwidth parameter value for the high-power DC
supply to improve the output voltage response speed. To reduce the DC supply
ripple, a control strategy is designed for a single module to adaptively adjust
the duty cycle compensation according to the output feedback value. When
multiple modules are connected in parallel, a Hierarchical Delay Current
Sharing Control (HDCSC) strategy for centralized controllers is proposed to
make the peaks and valleys of different modules offset each other. Finally, the
proposed method is verified by designing a 42V/12000A high-power DC supply, and
the results demonstrate that the proposed method is effective in improving the
system output voltage response speed and reducing the voltage ripple, which has
significant practical engineering application value.Comment: Accepted by IEEE Transactions on Power Electronic
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