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Decentralized Estimation and Control for
Multisensor Systems explores the problem of developing scalable,
decentralized estimation and control algorithms for linear and
nonlinear multisensor systems. Such algorithms have extensive
applications in modular robotics and complex or large scale
systems, including the Mars Rover, the Mir station, and Space
Shuttle Columbia.
Most existing algorithms use some form of hierarchical or
centralized structure for data gathering and processing. In
contrast, in a fully decentralized system, all information is
processed locally. A decentralized data fusion system includes a
network of sensor nodes - each with its own processing facility,
which together do not require any central processing or central
communication facility. Only node-to-node communication and local
system knowledge are permitted.
Algorithms for decentralized data fusion systems based on the
linear information filter have been developed, obtaining
decentrally the same results as those in a conventional centralized
data fusion system. However, these algorithms are limited,
indicating that existing decentralized data fusion algorithms have
limited scalability and are wasteful of communications and
computation resources.
Decentralized Estimation and Control for
Multisensor Systems aims to remove current limitations in
decentralized data fusion algorithms and to extend the
decentralized principle to problems involving local control and
actuation.
The text discusses:
Generalizing the linear Information filter to the problem of
estimation for nonlinear systems
Developing a decentralized form of the algorithm
Solving the problem of fully connected topologies by using
generalized model distribution where the nodal system involves only
locally relevant states
Reducing computational requirements by using smaller local model
sizes
Defining internodal communication
Developing estimation algorithms for different models
Applying the decentralized algorithms to the problem of
decentralized control
Demonstrating the theory to a modular wheeled mobile robot, a
vehicle system with nonlinear kinematics and distributed means of
acquiring information
Extending the applications to other robotic systems and large scale
systems
Decentralized Estimation and Control for
Multisensor Systems addresses how decentralized estimation and
control systems are rapidly becoming indispensable tools in a
diverse range of applications - such as process control systems,
aerospace, and mobile robotics - providing a self-contained,
dynamic resource concerning electrical and mechanical engineering.
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