國立虎尾科技大學 |

Robust Adaptive Nonlinear Control Strategies for Advanced Aerial Vehicles : = Theory and Applications.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Robust Adaptive Nonlinear Control Strategies for Advanced Aerial Vehicles :/
Reminder of title:	Theory and Applications.
Author:	Liu, Dakai.
Description:	1 online resource (137 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
Contained By:	Dissertations Abstracts International85-04B.
Subject:	Engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798380581219

Robust Adaptive Nonlinear Control Strategies for Advanced Aerial Vehicles : = Theory and Applications.
Liu, Dakai.

Robust Adaptive Nonlinear Control Strategies for Advanced Aerial Vehicles :Theory and Applications. - 1 online resource (137 pages)

Source: Dissertations Abstracts International, Volume: 85-04, Section: B.

Thesis (Ph.D.)--Stevens Institute of Technology, 2023.

Includes bibliographical references

The ongoing evolution of the aerospace industry has seen a significant rise in the development of advanced aerial vehicles, such as reusable launch vehicles (RLVs) and hypersonic flight vehicles (HFVs). Despite the potential benefits of these vehicles, their design presents substantial challenges, including complicated aerodynamics, strong nonlinearities, large flight envelopes, and demanding flight environments. This dissertation aims to enhance robust adaptive control methodologies to render them more suitable for practical implementation in advanced aerial vehicles.The research comprises the development of two advanced adaptive higher-order sliding mode control (SMC) methodologies for reentry RLV attitude control and an adaptive robust backstepping control strategy for HFV control. The methodologies address various challenges, including modeling uncertainties, disturbances, actuator faults, control input saturation, and state constraints.First, a novel adaptive second-order nonsingular fast terminal sliding mode fault-tolerant control scheme is proposed for RLVs during reentry. This control law eliminates initial phase oscillations, does not require prior knowledge of disturbance upper bounds, and offers increased robustness compared to existing methods. Furthermore, it addresses modeling uncertainties, disturbances, and actuator faults, which are significant concerns in RLV control.Then, a two-loop control scheme for RLV attitude control is introduced as an alternative to the terminal SMC-based approach. The proposed outer-loop and inner-loop controllers are extended to be multivariable and input-constrained methods, further enhancing their suitability for real-world applications above and beyond the method in Chapter 1. This control scheme adeptly addresses prevalent challenges in RLV attitude control systems, including input constraints, state-dependent disturbances, and multivariable control.A comprehensive state-constrained control strategy for HFVs is formulated, which, for the first time, simultaneously addresses multiple challenges, including actuator faults, control input saturation, aerodynamic uncertainties, and both nominal and stochastic external disturbances. An adaptive backstepping control strategy is adopted, and neural networks are implemented to guarantee its sufficient robustness. This control strategy ensures proper operation of the vehicle by restricting specific states to predefined ranges, making it highly practical for real-world HFV control systems.In conclusion, this dissertation contributes to the advancement of robust adaptive control methodologies for advanced aerial vehicles, addressing an extensive array of challenges and demonstrating their potential suitability in real-world contexts. Comparative simulation tests are also included to validate these findings.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380581219Subjects--Topical Terms:

561152
Engineering.
Subjects--Index Terms:

Advanced aerial vehiclesIndex Terms--Genre/Form:

554714
Electronic books.

Robust Adaptive Nonlinear Control Strategies for Advanced Aerial Vehicles : = Theory and Applications.
LDR:04294ntm a22004097 4500 001 1145119
005 20240617111349.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798380581219
035 $a (MiAaPQ)AAI30524821
035 $a AAI30524821
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Liu, Dakai. $3 1470338
245 1 0 $a Robust Adaptive Nonlinear Control Strategies for Advanced Aerial Vehicles : $b Theory and Applications.
264 0 $c 2023
300 $a 1 online resource (137 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-04, Section: B.
500 $a Advisor: Esche, Sven.
502 $a Thesis (Ph.D.)--Stevens Institute of Technology, 2023.
504 $a Includes bibliographical references
520 $a The ongoing evolution of the aerospace industry has seen a significant rise in the development of advanced aerial vehicles, such as reusable launch vehicles (RLVs) and hypersonic flight vehicles (HFVs). Despite the potential benefits of these vehicles, their design presents substantial challenges, including complicated aerodynamics, strong nonlinearities, large flight envelopes, and demanding flight environments. This dissertation aims to enhance robust adaptive control methodologies to render them more suitable for practical implementation in advanced aerial vehicles.The research comprises the development of two advanced adaptive higher-order sliding mode control (SMC) methodologies for reentry RLV attitude control and an adaptive robust backstepping control strategy for HFV control. The methodologies address various challenges, including modeling uncertainties, disturbances, actuator faults, control input saturation, and state constraints.First, a novel adaptive second-order nonsingular fast terminal sliding mode fault-tolerant control scheme is proposed for RLVs during reentry. This control law eliminates initial phase oscillations, does not require prior knowledge of disturbance upper bounds, and offers increased robustness compared to existing methods. Furthermore, it addresses modeling uncertainties, disturbances, and actuator faults, which are significant concerns in RLV control.Then, a two-loop control scheme for RLV attitude control is introduced as an alternative to the terminal SMC-based approach. The proposed outer-loop and inner-loop controllers are extended to be multivariable and input-constrained methods, further enhancing their suitability for real-world applications above and beyond the method in Chapter 1. This control scheme adeptly addresses prevalent challenges in RLV attitude control systems, including input constraints, state-dependent disturbances, and multivariable control.A comprehensive state-constrained control strategy for HFVs is formulated, which, for the first time, simultaneously addresses multiple challenges, including actuator faults, control input saturation, aerodynamic uncertainties, and both nominal and stochastic external disturbances. An adaptive backstepping control strategy is adopted, and neural networks are implemented to guarantee its sufficient robustness. This control strategy ensures proper operation of the vehicle by restricting specific states to predefined ranges, making it highly practical for real-world HFV control systems.In conclusion, this dissertation contributes to the advancement of robust adaptive control methodologies for advanced aerial vehicles, addressing an extensive array of challenges and demonstrating their potential suitability in real-world contexts. Comparative simulation tests are also included to validate these findings.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Engineering. $3 561152
650 4 $a Automotive engineering. $3 1104081
650 4 $a Aerospace engineering. $3 686400
650 4 $a Mechanical engineering. $3 557493
653 $a Advanced aerial vehicles
653 $a Control strategy
653 $a Two-loop control scheme
653 $a Robust adaptive control
653 $a Input constraints
655 7 $a Electronic books. $2 local $3 554714
690 $a 0537
690 $a 0540
690 $a 0548
690 $a 0538
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Stevens Institute of Technology. $b Mechanical Engineer. $3 1178936
773 0 $t Dissertations Abstracts International $g 85-04B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30524821 $z click for full text (PQDT)