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Adaptive Critic Autopilot Design of Bank-to-Turn Missiles Using Fuzzy Basis Function Networks.

Authors :
Lin, Chuan-Kai
Source :
IEEE Transactions on Systems, Man & Cybernetics: Part B. Apr2005, Vol. 35 Issue 2, p197-207. 11p.
Publication Year :
2005

Abstract

A new adaptive critic autopilot design for bank-to. turn missiles is presented. In this paper, the architecture of adaptive critic learning scheme contains a fuzzy-basis-function-network based associative search element (ASE), which is employed to approximate nonlinear and complex functions of bank-to-turn missiles, and an adaptive critic element (ACE) generating the reinforcement signal to tune the associative search element. In the design of the adaptive critic autopilot, the control law receives signals from a fixed gain controller, an ASE and an adaptive robust element, which can eliminate approximation errors and disturbances. Traditional adaptive critic reinforcement learning is the problem faced by an agent that must learn behavior through trial-and-error interactions with a dynamic environment, however, the proposed tuning algorithm can significantly shorten the learning time by on-line tuning all parameters of fuzzy basis functions and weights of ASE and ACE. Moreover, the weight updating law derived from the Lyapunov stability theory is capable of guaranteeing both tracking performance and stability. Computer simulation results confirm the effectiveness of the proposed adaptive critic autopilot. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10834419
Volume :
35
Issue :
2
Database :
Academic Search Index
Journal :
IEEE Transactions on Systems, Man & Cybernetics: Part B
Publication Type :
Academic Journal
Accession number :
16556518
Full Text :
https://doi.org/10.1109/TSMCB.2004.842246