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Nonlinear robust neuro-adaptive flight control for hypersonic vehicles with state constraints

Sachan, K and Padhi, R (2020) Nonlinear robust neuro-adaptive flight control for hypersonic vehicles with state constraints. In: Control Engineering Practice, 102 .

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Official URL: https://doi.org/10.1016/j.conengprac.2020.104526

Abstract

This paper presents a new nonlinear robust neuro-adaptive state-constrained control formulation for effectively controlling a hypersonic flight vehicle in cruise. The proposed controller ensures that the vehicle velocity, attitude and angular body rates remain bounded within the prescribed limits. The asymptotic stability of the closed-loop system in presence of imposed state constraints is shown following barrier Lyapunov function based stability theory. A Sobolev norm-based adaptive control scheme is used along with the nominal controller to ensure the stability of the vehicle in the presence of model uncertainties (as high as 30). The adaptive control formulation leads to quick learning with much lesser transients and is robust enough not to violate the imposed state-constraints. The effectiveness of the proposed nonlinear control design is illustrated by carrying out a large number of Monte-Carlo like randomized high fidelity six-degree-of-freedom (Six-DOF) simulation studies. © 2020 Elsevier Ltd

Item Type: Journal Article
Publication: Control Engineering Practice
Publisher: Elsevier Ltd
Additional Information: Copyright of this article belongs to Elsevier Ltd
Keywords: Adaptive control systems; Asymptotic stability; Closed loop systems; Controllers; Degrees of freedom (mechanics); Hypersonic aerodynamics; Lyapunov functions; Monte Carlo methods; Uncertainty analysis, Adaptive control schemes; Adaptive flight controls; Constrained controls; Hypersonic flight vehicles; Model uncertainties; Nonlinear control design; Simulation studies; Six degree-of-freedom, Hypersonic vehicles
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 06 Apr 2021 09:53
Last Modified: 06 Apr 2021 09:53
URI: http://eprints.iisc.ac.in/id/eprint/65919

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