<p>YUNMIN ZHU In the past two decades, multi sensor or multi-source information fusion techΒ niques have attracted more and more attention in practice, where observations are processed in a distributed manner and decisions or estimates are made at the individual processors, and processed data (or co
Decentralized Estimation and Control for Multisensor Systems
β Scribed by Arthur G.O. Mutambara
- Publisher
- CRC Press
- Year
- 1998
- Tongue
- English
- Leaves
- 126
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Decentralized Estimation and Control forMultisensor 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 forMultisensor 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 systemsDeveloping a decentralized form of the algorithmSolving the problem of fully connected topologies by using generalized model distribution where the nodal system involves only locally relevant statesReducing computational requirements by using smaller local model sizesDefining internodal communicationDeveloping estimation algorithms for different modelsApplying the decentralized algorithms to the problem of decentralized controlDemonstrating the theory to a modular wheeled mobile robot, a vehicle system with nonlinear kinematics and distributed means of acquiring informationExtending the applications to other robotic systems and large scale systemsDecentralized Estimation and Control forMultisensor 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.
π SIMILAR VOLUMES
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