Control-Oriented Fuzzy Multi-Model Identification of a Highly Nonlinear Missile

A novel fuzzy identification algorithm is introduced that is based on fuzzy interpolation of locally linear models obtained from a nonlinear system. Fuzzy clustering is employed to automatically decompose operating envelope of a nonlinear system into optimal number of operating partitions by means o...

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Bibliographic Details
Main Authors: Hashemi, S.V., Mehrabian, A.R., Roshanian, J.
Format: Conference Proceeding
Language:English
Subjects:
Aerospace control
Automatic control
Clustering algorithms
Fuzzy clustering
Fuzzy control
Fuzzy sets
Fuzzy systems
Gain scheduling
Interpolation
Linear parameter-varying systems
Missiles
Nonlinear systems
Partitioning algorithms
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Description
Summary:A novel fuzzy identification algorithm is introduced that is based on fuzzy interpolation of locally linear models obtained from a nonlinear system. Fuzzy clustering is employed to automatically decompose operating envelope of a nonlinear system into optimal number of operating partitions by means of optimal number of rules in a Tagaki-Sugeno fuzzy set direct realistic extension to flight control is introduced and applied on a tail-controlled skid-to-turn missile. The fuzzy model is evaluated using simulations of the complete nonlinear model. Simulation studies are reported to demonstrate merits of fuzzy systems in handling the demanding nonlinear modeling task
ISSN:1541-1672
1941-1294
DOI:10.1109/IS.2006.348440