2 research outputs found
A Survey on Blockchain Technology and Its Potential Applications in Distributed Control and Cooperative Robots
As a disruptive technology, blockchain, particularly its original form of
bitcoin as a type of digital currency, has attracted great attentions. The
innovative distributed decision making and security mechanism lay the technical
foundation for its success, making us consider to penetrate the power of
blockchain technology to distributed control and cooperative robotics, in which
the distributed and secure mechanism is also highly demanded. Actually,
security and distributed communication have long been unsolved problems in the
field of distributed control and cooperative robotics. It has been reported on
the network failure and intruder attacks of distributed control and
multi-robotic systems. Blockchain technology provides promise to remedy this
situation thoroughly. This work is intended to create a global picture of
blockchain technology on its working principle and key elements in the language
of control and robotics, to provide a shortcut for beginners to step into this
research field.Comment: 10 pages, 6 figure
Delay and Packet-Drop Tolerant Multi-Stage Distributed Average Tracking in Mean Square
This paper studies the distributed average tracking problem pertaining to a
discrete-time linear time-invariant multi-agent network, which is subject to,
concurrently, input delays, random packet-drops, and reference noise. The
problem amounts to an integrated design of delay and packet-drop tolerant
algorithm and determining the ultimate upper bound of the tracking error
between agents' states and the average of the reference signals. The
investigation is driven by the goal of devising a practically more attainable
average tracking algorithm, thereby extending the existing work in the
literature which largely ignored the aforementioned uncertainties. For this
purpose, a blend of techniques from Kalman filtering, multi-stage consensus
filtering, and predictive control is employed, which gives rise to a simple yet
comepelling distributed average tracking algorithm that is robust to
initialization error and allows the trade-off between communication/computation
cost and stationary-state tracking error. Due to the inherent coupling among
different control components, convergence analysis is significantly
challenging. Nevertheless, it is revealed that the allowable values of the
algorithm parameters rely upon the maximal degree of an expected network, while
the convergence speed depends upon the second smallest eigenvalue of the same
network's topology. The effectiveness of the theoretical results is verified by
a numerical example