Game estimators for air combat games with unknown enemy inputs

In an air combat game, a naive application of Kalman filtering does not work, because direct information about the enemy's inputs is not available. In this paper, we present two different approaches in estimating the states of the friendly as well as enemy forces based on the output observation...

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Published in2003 American Control Conference; Denver, CO; USA; 4-6 June 2003 Vol. 6; pp. 5381 - 5387 vol.6
Main Authors Caliskan, F., Mukai, H., Katz, I.N., Tanikawa, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Adaptive control
Control systems
Force control
Force feedback
Force sensors
Minimax techniques
Observers
Optimal control
Performance analysis
State estimation
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Summary:In an air combat game, a naive application of Kalman filtering does not work, because direct information about the enemy's inputs is not available. In this paper, we present two different approaches in estimating the states of the friendly as well as enemy forces based on the output observation and the friendly control inputs, when the enemy inputs are not available. The two methods are our extension of the Kalman filter due to Darouach et al. and the unknown input-decoupling observer due to Chen and Patton. We perform their stochastic simulation in the context of a game-theoretic feedback controller and compare their performance under noise.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780780378964
0780378962
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2003.1242584