Robust auto-landing of fixed-wing UAVs using neuro-adaptive design

Ambati, R Pradeep and Padhi, Radhakant (2017) Robust auto-landing of fixed-wing UAVs using neuro-adaptive design. In: CONTROL ENGINEERING PRACTICE, 60 . pp. 218-232.

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Abstract

An innovative neuro-adaptive design philosophy is presented in this paper embedding a Sobolev norm based Lyapunov function for directional learning of the unknown function, which is capable of learning both the unknown function in the system model and its Jacobian. This facilitates fast learning (model adaptation) without much of transient effects. The updated model is then used in the framework of dynamic inversion to design the guidance (outer) loop as well as the control (inner) loop. Using this philosophy a robust adaptive nonlinear guidance and control design is presented for robust automatic landing. The performance of the proposed approach is successfully verified through numerous simulation studies using the six degrees-of-freedom (six-DOF) nonlinear model of a prototype UAV. All possible disturbance effects that arise in practice, namely modeling inaccuracies, wind disturbances and ground effect, have been considered in the simulation studies. (C) 2016 Elsevier Ltd. All rights reserved.

Item Type:	Journal Article
Publication:	CONTROL ENGINEERING PRACTICE
Publisher:	PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
Additional Information:	Copy right for this article belongs to the PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
Department/Centre:	Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited:	20 May 2017 05:02
Last Modified:	20 May 2017 05:02
URI:	http://eprints.iisc.ac.in/id/eprint/56879

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