Decentralized Estimation and Control for Multisensor Systems

ISBN-13: 9780849318658 / Angielski / Twarda / 1998 / 248 str.

Arthur Mutambara

Opis

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.

Spis treści

Introduction
Background
Motivation
Problem Statement
Approach
Principal Contributions
Book Outline
Estimation and Information Space
Introduction
The Kalman Filter
The Information Filter
The Extended Kalman Filter (EKF)
The Extended Information Filter (EIF)
Examples of Estimation in Nonlinear Systems
Summary
Decentralized Estimation for Multisensor Systems
Introduction
Multisensor Systems
Decentralized Systems
Decentralized Estimators
The Limitations of Fully Connected Decentralization
Summary
Scalable Decentralized Estimation
Introduction
An Extended Example
The Moore-Penrose Generalized Inverse: T+
Generalized Internodal Transformation
Special Cases of Tji(k)
Distributed and Decentralized Filters
Summary
Scalable Decentralized Control
Introduction
Optimal Stochastic Control
Decentralized Multisensor Based Control
Simulation Example
Summary
Multisensor Applications: A Wheeled Mobile Robot
Introduction
Wheeled Mobile Robot (WMR) Modeling
Decentralized WMR Control
Hardware Design and Construction
Software Development
On-Vehicle Software
Summary
Results and Performance Analysis
Introduction
System Performance Criteria
Simulation Results
WMR Experimental Results
Summary
Conclusions and Future Research
Introduction
Summary of Contributions
Research Appraisal
Future Research Directions
Bibliography

O autorze

Professor Arthur G.O. Mutambara- Arthur Mutambara is a robotics scientist, professor, and former Deputy Prime Minister of Zimbabwe. He is the Managing Director and CEO of the Africa Technology & Business Institute. Main research focus: wheeled mobile robots, decentralized communication in scalable flight formation, mechatronic design methodology, and modular robots.