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Lighter than Air RobotsControl

Lighter than Air Robots: Control [The control methods implemented on lighter than air robots lie in two categories: traditional control methods and advanced control methods. The traditional control methods achieve autonomous control goals via classical control algorithms. These control methods have the advantage of being easily implemented and providing reliable control performance while the weaknesses include the costs of computation to model the system and tuning the control parameters. The most basic nonlinear control laws are the On-off control and Gain scheduling. Most of the advanced control methods are faced with highly nonlinear and time varying control system, in which it is difficult to obtain an accurate dynamic model of the LTAR and the environment. Several control methods have been developed such as back stepping control, robust control, model-prediction control and other intelligent control methods.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Lighter than Air RobotsControl

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Publisher
Springer Netherlands
Copyright
© Springer Science+Business Media B.V. 2012
ISBN
978-94-007-2662-8
Pages
165 –217
DOI
10.1007/978-94-007-2663-5_5
Publisher site
See Chapter on Publisher Site

Abstract

[The control methods implemented on lighter than air robots lie in two categories: traditional control methods and advanced control methods. The traditional control methods achieve autonomous control goals via classical control algorithms. These control methods have the advantage of being easily implemented and providing reliable control performance while the weaknesses include the costs of computation to model the system and tuning the control parameters. The most basic nonlinear control laws are the On-off control and Gain scheduling. Most of the advanced control methods are faced with highly nonlinear and time varying control system, in which it is difficult to obtain an accurate dynamic model of the LTAR and the environment. Several control methods have been developed such as back stepping control, robust control, model-prediction control and other intelligent control methods.]

Published: Sep 6, 2011

Keywords: Linear Quadratic Regulator; Multiple Input Multiple Output System; Gain Schedule; Fault Tolerant Control; Fault Tree Analysis

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