Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (26)

Search Parameters:
Keywords = sweep-morphing

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
26 pages, 6918 KB  
Article
Coordinated Reentry Guidance with A* and Deep Reinforcement Learning for Hypersonic Morphing Vehicles Under Multiple No-Fly Zones
by Cunyu Bao, Xingchen Li, Weile Xu, Guojian Tang and Wen Yao
Aerospace 2025, 12(7), 591; https://doi.org/10.3390/aerospace12070591 - 30 Jun 2025
Viewed by 420
Abstract
Hypersonic morphing vehicles (HMVs), renowned for their adaptive structural reconfiguration and cross-domain maneuverability, confront formidable reentry guidance challenges under multiple no-fly zones, stringent path constraints, and nonlinear dynamics exacerbated by morphing-induced aerodynamic uncertainties. To address these issues, this study proposes a hierarchical framework [...] Read more.
Hypersonic morphing vehicles (HMVs), renowned for their adaptive structural reconfiguration and cross-domain maneuverability, confront formidable reentry guidance challenges under multiple no-fly zones, stringent path constraints, and nonlinear dynamics exacerbated by morphing-induced aerodynamic uncertainties. To address these issues, this study proposes a hierarchical framework integrating an A-based energy-optimal waypoint planner, a deep deterministic policy gradient (DDPG)-driven morphing policy network, and a quasi-equilibrium glide condition (QEGC) guidance law with continuous sliding mode control. The A* algorithm generates heuristic trajectories circumventing no-fly zones, reducing the evaluation function by 6.2% compared to greedy methods, while DDPG optimizes sweep angles to minimize velocity loss and terminal errors (0.09 km position, 0.01 m/s velocity). The QEGC law ensures robust longitudinal-lateral tracking via smooth hyperbolic tangent switching. Simulations demonstrate generalization across diverse targets (terminal errors < 0.24 km) and robustness under Monte Carlo deviations (0.263 ± 0.184 km range, −12.7 ± 42.93 m/s velocity). This work bridges global trajectory planning with real-time morphing adaptation, advancing intelligent HMV control. Future research will extend this framework to ascent/dive phases and optimize its computational efficiency for onboard deployment. Full article
(This article belongs to the Section Aeronautics)
Show Figures

Figure 1

22 pages, 6442 KB  
Article
An Efficient SDOF Sweep Wing Morphing Technology for eVTOL-UAV and Experimental Realization
by Palaniswamy Shanmugam, Parammasivam Kanjikovil Mahali and Samikkannu Raja
Drones 2025, 9(6), 435; https://doi.org/10.3390/drones9060435 - 14 Jun 2025
Viewed by 448
Abstract
The presented study demonstrates that UAVs can be flown with a morphing wing to develop essential aerodynamic efficiency without a tail structure, which decides the operational cost and flight safety. The mechanical control for morphing is discussed, where the system design, simulation, and [...] Read more.
The presented study demonstrates that UAVs can be flown with a morphing wing to develop essential aerodynamic efficiency without a tail structure, which decides the operational cost and flight safety. The mechanical control for morphing is discussed, where the system design, simulation, and experimental realization of ±15° SDOF sweep motion for a 7 kg eVTOL wing are detailed. The methodology, developed through a mathematical modeling of the mechanism’s kinematics and dynamics, is explained using Denavit–Hartenberg (D-H) convention, Lagrangian mechanics, and Euler–Lagrangian equations. The simulation and MBD analyses were performed in MATLAB R2021 and by Altair Motion Solve, respectively. The experiment was conducted on a dedicated test rig with two wing variants fitted with IMUs and an autopilot. The results from various methods were analyzed and experimentally compared to provide an accurate insight into the system’s design, modeling, and performance of the sweep morphing wing. The theoretical calculations by the mathematical model were compared with the test results. The sweep requirement is essential for eVTOL to have long endurance and multi-mission capabilities. Therefore, the developed sweep morphing mechanism is very useful, meeting such a demand. However, the results for three-dimensional morphing, operating sweep, pitch, and roll together are also presented, for the sake of completeness. Full article
Show Figures

Figure 1

23 pages, 6721 KB  
Article
Rigid–Elastic Coupling Dynamics of Morphing Wing Aircraft
by Siyu Hua, Xugang Wang and Zhongyuan Wang
Aerospace 2025, 12(4), 327; https://doi.org/10.3390/aerospace12040327 - 10 Apr 2025
Cited by 1 | Viewed by 2497
Abstract
This paper presents a rigid–elastic coupling dynamic model for a morphing aircraft with variable-sweep wings, developed using Kane’s method. The model accurately captures the interactions between flight dynamics and structural dynamics during morphing. To fully account for the coupling effects, we derive a [...] Read more.
This paper presents a rigid–elastic coupling dynamic model for a morphing aircraft with variable-sweep wings, developed using Kane’s method. The model accurately captures the interactions between flight dynamics and structural dynamics during morphing. To fully account for the coupling effects, we derive a morphing aircraft model consisting of a rigid fuselage and two elastic wings. Each wing is modeled as a straight beam undergoing small elastic deformations while experiencing large overall motions following the fuselage in space, along with variable-sweep rotations relative to the fuselage. These factors introduce uncertainties into the flight dynamics. To quantify the uncertainties caused by wing rotation, additional morphing forces and moments are introduced to describe morphing-induced uncertainties, while additional elastic forces and moments are defined to account for uncertainties arising from wing deformations. Numerical simulations are conducted across different models and morphing rates to analyze the dynamic characteristics. The results reveal that the elastic deformations of morphing wings significantly influence pitch angles, pitch rates, and wing vibrations, particularly during large-sweep transitions exceeding 45°. Additionally, slow morphing rates below 5°/s induce significant transient uncertainties due to elastic vibrations. These findings establish a quantitative relationship between morphing rate, vibration characteristics, and model uncertainties, providing valuable insights for trajectory tracking and attitude control in morphing aircraft. Full article
(This article belongs to the Section Aeronautics)
Show Figures

Figure 1

32 pages, 10874 KB  
Article
Advanced Cooperative Formation Control in Variable-Sweep Wing UAVs via the MADDPG–VSC Algorithm
by Zhengyang Cao and Gang Chen
Appl. Sci. 2024, 14(19), 9048; https://doi.org/10.3390/app14199048 - 7 Oct 2024
Viewed by 1791
Abstract
UAV technology is advancing rapidly, and variable-sweep wing UAVs are increasingly valuable because they can adapt to different flight conditions. However, conventional control methods often struggle with managing continuous action spaces and responding to dynamic environments, making them inadequate for complex multi-UAV cooperative [...] Read more.
UAV technology is advancing rapidly, and variable-sweep wing UAVs are increasingly valuable because they can adapt to different flight conditions. However, conventional control methods often struggle with managing continuous action spaces and responding to dynamic environments, making them inadequate for complex multi-UAV cooperative formation control tasks. To address these challenges, this study presents an innovative framework that integrates dynamic modeling with morphing control, optimized by the multi-agent deep deterministic policy gradient for two-sweep control (MADDPG–VSC) algorithm. This approach enables real-time sweep angle adjustments based on current flight states, significantly enhancing aerodynamic efficiency and overall UAV performance. The precise motion state model for wing morphing developed in this study underpins the MADDPG–VSC algorithm’s implementation. The algorithm not only optimizes multi-UAV formation control efficiency but also improves obstacle avoidance, attitude stability, and decision-making speed. Extensive simulations and real-world experiments consistently demonstrate that the proposed algorithm outperforms contemporary methods in multiple aspects, underscoring its practical applicability in complex aerial systems. This study advances control technologies for morphing-wing UAV formation and offers new insights into multi-agent cooperative control, with substantial potential for real-world applications. Full article
(This article belongs to the Special Issue Collaborative Learning and Optimization Theory and Its Applications)
Show Figures

Figure 1

18 pages, 16152 KB  
Article
Characterization of Wing Kinematics by Decoupling Joint Movement in the Pigeon
by Yishi Shen, Shi Zhang, Weimin Huang, Chengrui Shang, Tao Sun and Qing Shi
Biomimetics 2024, 9(9), 555; https://doi.org/10.3390/biomimetics9090555 - 15 Sep 2024
Cited by 3 | Viewed by 2312
Abstract
Birds have remarkable flight capabilities due to their adaptive wing morphology. However, studying live birds is time-consuming and laborious, and obtaining information about the complete wingbeat cycle is difficult. To address this issue and provide a complete dataset, we recorded comprehensive motion capture [...] Read more.
Birds have remarkable flight capabilities due to their adaptive wing morphology. However, studying live birds is time-consuming and laborious, and obtaining information about the complete wingbeat cycle is difficult. To address this issue and provide a complete dataset, we recorded comprehensive motion capture wing trajectory data from five free-flying pigeons (Columba livia). Five key motion parameters are used to quantitatively characterize wing kinematics: flapping, sweeping, twisting, folding and bending. In addition, the forelimb skeleton is mapped using an open-chain three-bar mechanism model. By systematically evaluating the relationship of joint degrees of freedom (DOFs), we configured the model as a 3-DOF shoulder, 1-DOF elbow and 2-DOF wrist. Based on the correlation analysis between wingbeat kinematics and joint movement, we found that the strongly correlated shoulder and wrist roll within the stroke plane cause wing flap and bending. There is also a strong correlation between shoulder, elbow and wrist yaw out of the stroke plane, which causes wing sweep and fold. By simplifying the wing morphing, we developed three flapping wing robots, each with different DOFs inside and outside the stroke plane. This study provides insight into the design of flapping wing robots capable of mimicking the 3D wing motion of pigeons. Full article
(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots: Second Edition)
Show Figures

Figure 1

18 pages, 5315 KB  
Article
Investigation of a Tube-Launched Unmanned Aerial Vehicle with a Variable-Sweep Wing
by Peng Si, Mingjian Wu, Yongqing Huo and Zhilin Wu
Drones 2024, 8(9), 474; https://doi.org/10.3390/drones8090474 - 10 Sep 2024
Cited by 8 | Viewed by 3290
Abstract
Foldable wings are designed for tube-launched unmanned aerial vehicles (UAVs), aiming to improve portability and meet launch platform requirements. However, conventional tube-launched UAVs cannot operate across the wide speed ranges required for the performance of multiple missions, due to the fixed configuration of [...] Read more.
Foldable wings are designed for tube-launched unmanned aerial vehicles (UAVs), aiming to improve portability and meet launch platform requirements. However, conventional tube-launched UAVs cannot operate across the wide speed ranges required for the performance of multiple missions, due to the fixed configuration of their wings after launch. This study therefore proposes a tube-launched UAV which can change wing-sweep angle to expand the flight speed range and enhance the UAV’s agility. A computational aerodynamics method is employed to assess the transient aerodynamic performance of the UAV during the sweep morphing process. The simulation results indicate that the transient aerodynamic forces generate a dynamic hysteresis loop around the quasi-steady data. The lift and drag coefficients exhibit maximum relative deviations of 18.5% and 12.7% from the quasi-steady data for the sweep morphing period of 0.5 s. The hysteresis effect of the flow structure, rather than the additional velocity resulting from wing-sweep morphing, is the major contributor to the aerodynamic hysteresis loop. Compared to the conventional tube-launched UAVs, the proposed tube-launched UAV with a variable-sweep wing shows a wider flight speed range, from 22.59 to 90.12 m/s, and achieves an 82.84% increase in loitering speed. To verify the effectiveness of the wing-sweeping concept, a prototype was developed, and a flight test was carried out. The test data obtained from flight control system agree well with the simulation data, which demonstrates the feasibility and effectiveness of the variable-sweep wing in widening the speed range for tube-launched UAVs. This work can provide a reference for the design of tube-launched UAVs for wide speed range flight. Full article
Show Figures

Figure 1

18 pages, 11937 KB  
Article
CGull: A Non-Flapping Bioinspired Composite Morphing Drone
by Peter L. Bishay, Alex Rini, Moises Brambila, Peter Niednagel, Jordan Eghdamzamiri, Hariet Yousefi, Joshua Herrera, Youssef Saad, Eric Bertuch, Caleb Black, Donovan Hanna and Ivan Rodriguez
Biomimetics 2024, 9(9), 527; https://doi.org/10.3390/biomimetics9090527 - 31 Aug 2024
Cited by 3 | Viewed by 3242
Abstract
Despite the tremendous advances in aircraft design that led to successful powered flights of aircraft as heavy as the Antonov An-225 Mriya, which weighs 640 tons, or as fast as the NASA-X-43A, which reached a record of Mach 9.6, many characteristics of bird [...] Read more.
Despite the tremendous advances in aircraft design that led to successful powered flights of aircraft as heavy as the Antonov An-225 Mriya, which weighs 640 tons, or as fast as the NASA-X-43A, which reached a record of Mach 9.6, many characteristics of bird flight have yet to be utilized in aircraft designs. These characteristics enable various species of birds to fly efficiently in gusty environments and rapidly change their momentum in flight without having modern thrust vector control (TVC) systems. Vultures and seagulls, as examples of expert gliding birds, can fly for hours, covering more than 100 miles, without a single flap of their wings. Inspired by the Great Black-Backed Gull (GBBG), this paper presents “CGull”, a non-flapping unmanned aerial vehicle (UAV) with wing and tail morphing capabilities. A coupled two degree-of-freedom (DOF) morphing mechanism is used in CGull’s wings to sweep the middle wing forward and the outer feathered wing backward, replicating the GBBG’s wing deformation. A modular two DOF mechanism enables CGull to pitch and tilt its tail. A computational model was first developed in MachUpX to study the effects of wing and tail morphing on the generated forces and moments. Following the biological construction of birds’ feathers and bones, CGull’s structure is mainly constructed from carbon-fiber composite shells. The successful flight test of the proof-of-concept physical model proved the effectiveness of the proposed morphing mechanisms in controlling the UAV’s path. Full article
Show Figures

Graphical abstract

31 pages, 4991 KB  
Article
Finite-Time Convergence Guidance Law for Hypersonic Morphing Vehicle
by Dongdong Yao and Qunli Xia
Aerospace 2024, 11(8), 680; https://doi.org/10.3390/aerospace11080680 - 18 Aug 2024
Cited by 4 | Viewed by 1241
Abstract
Aiming at the interception constraint posed by defensive aircrafts against hypersonic morphing vehicles (HMVs) during the terminal guidance phase, this paper designed a guidance law with the finite-time convergence theory and control allocation methods based on the event-triggered theory, achieving evasion of the [...] Read more.
Aiming at the interception constraint posed by defensive aircrafts against hypersonic morphing vehicles (HMVs) during the terminal guidance phase, this paper designed a guidance law with the finite-time convergence theory and control allocation methods based on the event-triggered theory, achieving evasion of the defensive aircraft and targeting objectives for a morphing vehicle in the terminal guidance phase. Firstly, this paper established the aircraft motion model; the relative motion relationships between HMV, defensive aircraft, and target; and the control equations for the guidance system. Secondly, a guidance law with finite-time convergence was designed, establishing a controller with the angle between the aircraft–target–defense aircraft triplet as the state variable and lift as the control variable. By ensuring the angle was non-zero, the aircraft maintained a certain relative distance from the defense aircraft, achieving evasion of interception. The delay characteristic of the aircraft’s flight controller was considered, analyzing its delay stability and applying control compensation. Thirdly, a multi-model switching control allocation method based on an event-triggered mechanism was designed. Optimal attack and bank angles were determined based on acceleration control variables, considering different sweep angles. Finally, simulations were conducted to validate the effectiveness and robustness of the designed guidance laws. Full article
Show Figures

Figure 1

2 pages, 128 KB  
Abstract
CGull: A Non-Flapping Seagull-Inspired Composite Morphing Drone
by Peter L. Bishay, Moises Brambila, Alex Rini, Peter Niednagel, Jordan Eghdamzamiri, Hariet Yousefi, Joshua Herrera, Eric Bertuch, Caleb Black, Donovan Hanna, Ivan Rodriguez, Youssef Saad, Sebastian Campos, Aramar Arias-Rodas, Trent Bird and Behafarin Sharifi
Proceedings 2024, 107(1), 17; https://doi.org/10.3390/proceedings2024107017 - 15 May 2024
Viewed by 587
Abstract
Introduction: Many avian species are well equipped for dynamic flight with flexible morphing wings and tails that optimize aerodynamic performance across various environmental conditions [...] Full article
(This article belongs to the Proceedings of The 1st International Online Conference on Biomimetics)
19 pages, 1571 KB  
Article
Trajectory Tracking Control of Variable Sweep Aircraft Based on Reinforcement Learning
by Rui Cao and Kelin Lu
Biomimetics 2024, 9(5), 263; https://doi.org/10.3390/biomimetics9050263 - 27 Apr 2024
Cited by 2 | Viewed by 2078
Abstract
An incremental deep deterministic policy gradient (IDDPG) algorithm is devised for the trajectory tracking control of a four-wing variable sweep (FWVS) aircraft with uncertainty. The IDDPG algorithm employs the line-of-sight (LOS) method for path tracking, formulates a reward function based on position and [...] Read more.
An incremental deep deterministic policy gradient (IDDPG) algorithm is devised for the trajectory tracking control of a four-wing variable sweep (FWVS) aircraft with uncertainty. The IDDPG algorithm employs the line-of-sight (LOS) method for path tracking, formulates a reward function based on position and attitude errors, and integrates long short-term memory (LSTM) units into IDDPG algorithm to enhance its adaptability to environmental changes during flight. Finally, environmental disturbance factors are introduced in simulation to validate the designed controller’s ability to track climbing trajectories of morphing aircraft in the presence of uncertainty. Full article
Show Figures

Figure 1

16 pages, 1251 KB  
Article
Autonomous Shape Decision Making of Morphing Aircraft with Improved Reinforcement Learning
by Weilai Jiang, Chenghong Zheng, Delong Hou, Kangsheng Wu and Yaonan Wang
Aerospace 2024, 11(1), 74; https://doi.org/10.3390/aerospace11010074 - 12 Jan 2024
Cited by 3 | Viewed by 2213
Abstract
The autonomous shape decision-making problem of a morphing aircraft (MA) with a variable wingspan and sweep angle is studied in this paper. Considering the continuity of state space and action space, a more practical autonomous decision-making algorithm framework of MA is designed based [...] Read more.
The autonomous shape decision-making problem of a morphing aircraft (MA) with a variable wingspan and sweep angle is studied in this paper. Considering the continuity of state space and action space, a more practical autonomous decision-making algorithm framework of MA is designed based on the deep deterministic policy gradient (DDPG) algorithm. Furthermore, the DDPG with a task classifier (DDPGwTC) algorithm is proposed in combination with the long short-term memory (LSTM) network to improve the convergence speed of the algorithm. The simulation results show that the shape decision-making algorithm based on the DDPGwTC enables MA to adopt the optimal morphing strategy in different task environments with higher autonomy and environmental adaptability, which verifies the effectiveness of the proposed algorithm. Full article
(This article belongs to the Special Issue Cross-Domain Intelligent Flight Vehicle Design)
Show Figures

Figure 1

18 pages, 3890 KB  
Article
An Intelligent Autonomous Morphing Decision Approach for Hypersonic Boost-Glide Vehicles Based on DNNs
by Linfei Hou, Honglin Liu, Ting Yang, Shuaibin An and Rui Wang
Aerospace 2023, 10(12), 1008; https://doi.org/10.3390/aerospace10121008 - 30 Nov 2023
Cited by 5 | Viewed by 2135
Abstract
In addressing the morphing problem in vehicle flight, some scholars have primarily employed reinforcement learning methods to make morphing decisions based on task. However, they have not considered the constraints associated with the task process. The innovation of this article is that it [...] Read more.
In addressing the morphing problem in vehicle flight, some scholars have primarily employed reinforcement learning methods to make morphing decisions based on task. However, they have not considered the constraints associated with the task process. The innovation of this article is that it proposes an intelligent morphing decision method based on deep neural networks (DNNs) for the autonomous morphing decision problem of hypersonic boost-glide morphing vehicles under process constraints. Firstly, we established a dynamic model of a hypersonic boost-glide morphing vehicle with a continuously variable sweep angle. Then, in order to address the decision optimality problem considering errors and the heat flux density constraint problem during the gliding process, interference was introduced to the datum trajectory in segments. Subsequently, re-optimization was performed to generate a trajectory sample library, which was used to train an intelligent decision-maker using a DNN. The simulation results demonstrated that, compared with the conventional programmatic morphing approach, the intelligent morphing decision maker could dynamically determine the sweep angle based on the current flight state, leading to improved range while still adhering to the heat flux density constraint. This validates the effectiveness and robustness of the proposed intelligent decision-maker. Full article
(This article belongs to the Section Astronautics & Space Science)
Show Figures

Figure 1

13 pages, 13689 KB  
Article
3D-Printed Bio-Inspired Mechanisms for Bird-like Morphing Drones
by Peter L. Bishay, Matthew Brody, David Podell, Francisco Corte Garcia, Erik Munoz, Evette Minassian and Kevin Bradley
Appl. Sci. 2023, 13(21), 11814; https://doi.org/10.3390/app132111814 - 29 Oct 2023
Cited by 10 | Viewed by 4649
Abstract
Birds have unique flight characteristics unrivaled by even the most advanced drones due in part to their lightweight morphable wings and tail. Advancements in 3D-printing, servomotors, and composite materials are enabling more innovative airplane designs inspired by avian flight that could lead to [...] Read more.
Birds have unique flight characteristics unrivaled by even the most advanced drones due in part to their lightweight morphable wings and tail. Advancements in 3D-printing, servomotors, and composite materials are enabling more innovative airplane designs inspired by avian flight that could lead to optimized flight characteristics compared to traditional designs. Morphing technology aims to improve the aerodynamic and power efficiencies of aircraft by eliminating traditional control surfaces and implementing wings with significant shape-changing ability. This work proposes designs of 3D-printed, bio-inspired, non-flapping, morphing wing and tail mechanisms for unmanned aerial vehicles. The proposed wing design features a corrugated flexible 3D-printed structure to facilitate sweep morphing with expansion and contraction of the attached artificial feathers. The proposed tail feather expansion mechanism features a 3D-printed flexible structure with circumferential corrugation. The various available 3D-printing materials and the capability to print geometrically complex components have enabled the realization of the proposed morphing deformations without demanding relatively large actuation forces. Proof-of-concept models were manufactured and tested to demonstrate the effectiveness of the selected materials and actuators in achieving the desired morphing deformations that resemble those of seagulls. Full article
(This article belongs to the Special Issue Additive Manufacturing Technology and Applications for Aerospace)
Show Figures

Figure 1

28 pages, 12903 KB  
Article
Predictor–Corrector Guidance for a Hypersonic Morphing Vehicle
by Dongdong Yao and Qunli Xia
Aerospace 2023, 10(9), 795; https://doi.org/10.3390/aerospace10090795 - 11 Sep 2023
Cited by 6 | Viewed by 1817
Abstract
In an effort to address the problem of hypersonic morphing vehicles reaching the target while avoiding no-fly zones, an improved predictor–corrector guidance method is proposed. Firstly, the aircraft motion model and the constraint model are established. Then, the basic algorithm is given. The [...] Read more.
In an effort to address the problem of hypersonic morphing vehicles reaching the target while avoiding no-fly zones, an improved predictor–corrector guidance method is proposed. Firstly, the aircraft motion model and the constraint model are established. Then, the basic algorithm is given. The Q-learning method is used to design the attack angle and sweep angle scheme to ensure that the aircraft can fly over low-altitude zones. The B-spline curve is used to determine the locations of flight path points, and the bank angle scheme is designed using the predictor–corrector method, so that the aircraft can avoid high-altitude zones. Next, the Monte Carlo reinforcement learning (MCRL) method is used to improve the predictor–corrector method and a Deep Neural Network (DNN) is used to fit the reward function. The planning method in this paper realizes the use of a variable sweep angle, while the improved method further improves the performance of the trajectory, including the attainment of greater final speed and a smaller turning angle. The simulation results verify the effectiveness of the proposed algorithm. Full article
Show Figures

Figure 1

33 pages, 8401 KB  
Article
L1 Adaptive Control Based on Dynamic Inversion for Morphing Aircraft
by Lingquan Cheng, Yiyang Li, Jiayi Yuan, Jianliang Ai and Yiqun Dong
Aerospace 2023, 10(9), 786; https://doi.org/10.3390/aerospace10090786 - 7 Sep 2023
Cited by 9 | Viewed by 2722
Abstract
Morphing aircraft are able to keep optimal performance in diverse flight conditions. However, the change in geometry always leads to challenges in the design of flight controllers. In this paper, a new method for designing a flight controller for variable-sweep morphing aircraft is [...] Read more.
Morphing aircraft are able to keep optimal performance in diverse flight conditions. However, the change in geometry always leads to challenges in the design of flight controllers. In this paper, a new method for designing a flight controller for variable-sweep morphing aircraft is presented—dynamic inversion combined with L1 adaptive control. Firstly, the dynamics of the vehicle is analyzed and a six degrees of freedom (6DOF) nonlinear dynamics model based on multibody dynamics theory is established. Secondly, nonlinear dynamic inversion (NDI) and incremental nonlinear dynamic inversion (INDI) are then employed to realize decoupling control. Thirdly, linear quadratic regulator (LQR) technique and L1 adaptive control are adopted to design the adaptive controller in order to improve robustness to uncertainties and ensure the control accuracy. Finally, extensive simulation experiments are performed, wherein the demonstrated results indicate that the proposed method overcomes the drawbacks of conventional methods and realizes an improvement in control performance. Full article
(This article belongs to the Special Issue Flight Dynamics, Control & Simulation)
Show Figures

Figure 1

Back to TopTop