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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/556

Title: A Neuro–Adaptive Approach for Robust Control of High Performance Aircrafts with Parameter Inaccuracies.
Authors: Tripathi, Abha
Padhi, Radhakant
Keywords: Flight control
Dynamic inversion
Neuro- Adaptive design
High performance aircrafts
Issue Date: Dec-2008
Citation: Abha Tripathi and Radhakant Padhi, "A Neuro–Adaptive Approach for Robust Control of High Performance Aircrafts with Parameter Inaccuracies".
Abstract: For high performance aircrafts, the flight control system needs to be quite effective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addition, the control system must also be sufficiently robust to cater to possible parameter variations. The primary aim of this paper is to enhance the robustness of the controller for a HPA using neuro-adaptive control design. Here the architecture employs a network of Gaussian Radial basis functions to adaptively compensate for the ignored system dynamics. A stable weight mechanism is determined using Lyapunov theory. The network construction and performance of the resulting controller are illustrated through simulations with a low-fidelity six –DOF model of F16 that is available in open literature.
URI: http://hdl.handle.net/123456789/556
Appears in Collections:Conference Papers-Electrical

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