Parameter Identification for Application Within a Fault-Tolerant Flight Control System

Phillips, Kerri

doi:10.2514/6.2009-5723

Cited by 8 publications

(3 citation statements)

References 5 publications

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“…In recent years, for this purpose, adaptive controls are being studied extensively. In 2009, a team of researchers [5] performed parameter identification that was particularly used for fault-tolerance purpose. an active area of research.…”

Section: Reconfigurable Flight Controlmentioning

confidence: 99%

UAS Model Identification and Simulation to Support In-Flight Testing of Discrete Adaptive Fault-Tolerant Control Laws

Bakori¹,

Moncayo²

2020

AIAA Scitech 2020 Forum

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In mission-critical applications of unmanned and autonomous aerial systems(UAS), it is of significant importance to develop robust strategies for fault-tolerant systems that can countermeasure system degradation and consequently support the integration into the National Airspace (NAS). This thesis research illustrates the results of systems identification that is performed using DATCOM followed by the flight test data. This data is acquired from conducting an intensive flight testings program of a fixed-wing UAS to determine the state-space model of the aircraft. A discrete state-space system is reconstructed from these models to derive Auto-Regressive Moving-Average (ARMA) models used to design a Discrete Direct and Indirect Model Reference Adaptive Control. Description of the UAS, subsystems , and integration is presented in this thesis along with analysis of results from numerical simulation to support the design, development, and validation of adaptive control laws for fault tolerance.A set of performance metrics are defined to perform the analysis in terms of control effort, tracking performance, and reconfiguration of control laws under commonly occurring failures such as partial control surface damage, pilot-induced oscillations, and uncertain ice accretion. v ACKNOWLEDGMENT Though the following dissertation is an individual effort, I believe that it epitomizes my years of hard work, propensity to move forward and most importantly, people who have assisted me in this journey. Recapitulating my journey, I have nothing but utmost appreciation and gratitude for the valuable support, guidance and efforts of people. My passion for contributing to aerospace unmanned industry has been reinforced by a strong organizational resilience and academic guidance. Therefore, I would like to extend my gratitude to my Research advisor Dr. Hever Moncayo for directing me with his experience and aptitude and for being an exceptional coach in my scholastic life. My sincere appreciation towards my Advisory Committee , Dr.Richard Stansbury and Dr. Yan Tang for giving your valuable time and insights. An exceptional thanks to Michael Potash and Bill Russo for your enormous assistance with hardware and calmly noting every one of my inquiries. I would also like to offer gratitude to Dr. Gordan Leishman and Dr. Zheng Zang for their distinctive contribution in helping me calibrate air-data probe and allowing me to use the Subsonic Wind-Tunnel Facility. I acknowledge assistance from Rob, Austin, Ethan and Jeremy for being ever ready to be the test-pilot and not complaining about early morning flights. I likewise recognise contributions from Jorge Begue for providing helping hand in assembling the UAV. On board of this journey, there was unprecedented team of talented individuals that provided valuable expertise and their benevolent support in the advancement of the unmanned iii aerial vehicle thus I will be everlastingly thankful to my lab colleagues turned friends: An

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Section: Reconfigurable Flight Controlmentioning

confidence: 99%

UAS Model Identification and Simulation to Support In-Flight Testing of Discrete Adaptive Fault-Tolerant Control Laws

Bakori¹,

Moncayo²

2020

AIAA Scitech 2020 Forum

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“…For safe landing, control commands should maintain glide path, heading angle and speed as desired. 8 These requirements can be followed by open-loop control, where the pilot will execute landing manoeuvers manually. Also, closed-loop control can be used for landing solution in which control system automatically applies required command.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode controller based aircraft automatic landing for alternate profiles

Salahudden

Sanwale

Giri

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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In the present paper, different autonomous landing profiles are formulated and simulated. Generic landing is modelled first, wherein, approach and acquired runway heading is considered as same. The second-landing profile involves altitude hold when runway is not clear to land the aircraft. Expedited landing is the third profile modelled with a glide slope-maintained descent to reduce the ground distance required pre-touchdown. In either of the landing profiles, flare is kept the same. The merits and demerits with respect to the practicality of implementation of these profiles are then discussed. Each landing profile has been demonstrated using sliding mode controller (SMC). The asymptotic stability and finite-time proofs of the designed controller are shown using Lyapunov function. F-18 HARV aircraft is considered to test the efficacy of the formulated landing profiles. Expedited landing profile proposed here is a novel approach in which altitude descent gradient is maintained with helical descent path. Additionally, results of this approach show significant improvement in terms of possibility of initiating an unconventional and yet safe as well as economical method much nearer to the runway.

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“…In order to track the leader the follower UAV must be able to calculate the appropriate surface deflection commands in order to maintain the desired attitude developed within the OLC, this is done within the ILC 51 . The ILC was designed using Linear Quadratic (LQ) techniques which begin with the development of a linear aircraft model described in [52]. The LQ control laws were developed using the methods in [53].…”

Section: Innerloop Controlmentioning

confidence: 99%

Wind and Wake Sensing with UAV Formation Flight: System Development and Flight Testing

Larrabee¹

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Parameter Identification for Application Within a Fault-Tolerant Flight Control System

Cited by 8 publications

References 5 publications

UAS Model Identification and Simulation to Support In-Flight Testing of Discrete Adaptive Fault-Tolerant Control Laws

UAS Model Identification and Simulation to Support In-Flight Testing of Discrete Adaptive Fault-Tolerant Control Laws

Sliding mode controller based aircraft automatic landing for alternate profiles

Wind and Wake Sensing with UAV Formation Flight: System Development and Flight Testing

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