Aerodynamic optimization of a morphing UAV with variable sweep and variable span

Yang, Guan Tong; Tang, Sheng Jing; Guo, Ji Lin

doi:10.2495/csse140671

Cited by 6 publications

(5 citation statements)

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“…In [32], a quasi-LPV model of a missile has been derived using a simplified FS method, without giving an explicit solution for (8). In fact, for most cases, (8) will make x 1 be a part of varying parameters besides δ.…”

Section: An Improved Fs and Application On Muavmentioning

confidence: 99%

“…Different missions require UAVs with different characteristics, for example, scouting missions require long endurance [5] while attack missions require maneuverability [6]. Inspired by the biological nature of birds, the morphing UAV (MUAV), which has the ability to accommodate its wing shape to various mission requirements, has become the focus of research [6][7][8][9][10][11]. Birds have the ability to change the shape of their wings to adapt themselves to various flight environments and mission requirements.…”

Section: Introductionmentioning

confidence: 99%

“…Birds have the ability to change the shape of their wings to adapt themselves to various flight environments and mission requirements. Inspired by the biological nature of birds, the morphing UAV (MUAV), which has the ability to accommodate its wing shape to various mission requirements, has become the focus of research . With regard to realistic projects, the DARPA's Morphing Aerial Structure (MAS) is the most well known .…”

Section: Introductionmentioning

confidence: 99%

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Model and robust gain‐scheduled PID control of a bio‐inspired morphing UAV based on LPV method

Shao

et al. 2019

Asian Journal of Control

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In this paper, a linear parameter-varying (LPV)-based model and robust gainscheduled structural proportion integral and derivative (PID) control design solution are proposed and applied on a bio-inspired morphing wing unmanned aerial vehicle (UAV) for the morphing process. In the LPV model method, the authors propose an improved modeling method for LPV systems. The method combines partial linearization and function substitution. Using the proposed method, we can choose the varying parameters simply, thus creating a model that is more flexible and applicable. Then, a robust gain-scheduled structural PID control design method is given by introducing a structural matrix to design a structural PID controller, which is more consistent with the structure of the PID controller used in practice and has a simpler structure than representative ones in the existing literature. The simulation results show that the developed LPV morphing UAV model is able to catch the response of the original nonlinear model with a smaller error than the existing Jacobian linearization method and the designed controller can maintain stable flights in practice with satisfactory robustness and performance.

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Section: An Improved Fs and Application On Muavmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Model and robust gain‐scheduled PID control of a bio‐inspired morphing UAV based on LPV method

Shao

et al. 2019

Asian Journal of Control

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“…To study aerodynamics and design aircrafts, wind tunnels, especially the continuous transonic wind tunnel (CTWT), have become indispensable. Over the past two decades, the research and practical application of wind tunnels have received increasing attention, as they are widely applied in many fields based on aerodynamic theories [1,2] and in the design of many artifact including bridges [3], buildings [4], trains [5] and aircrafts [6][7][8]. It should be especially noted that wind tunnel experimentation has great significance for wind farm research, as it can help to model the inter-farm cluster interaction of the wind power base [9].…”

Section: Introductionmentioning

confidence: 99%

Mach Number Prediction for 0.6 m and 2.4 m Continuous Transonic Wind Tunnels

2023

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With the development of the design technology, more and more advanced and diverse wind tunnels have been constructed to match complex requirements. However, it is hard to design a precise physical model of a wind tunnel that can be controlled. In addition, if a new wind tunnel is designed, the experimental data may be insufficient to build a controlling model. This article reports research on the following two models: (1) for a 0.6 m continuous transonic wind tunnel supported by a large amount of historical data, the false nearest neighbor (FNN) algorithm was adopted to calculate the order of the input variables, and the nonlinear auto-regressive model with the exogenous inputs–backpropagation network (NARX-BP) was proposed to build its Mach number prediction model; (2) for a new 2.4 m continuous transonic wind tunnel with only a small amount of experimental data, the method of model migration, the input and output slope/bias correction–particle swarm optimization (IOSBC-PSO) algorithm, was developed to convert the old model of the 0.6 m wind tunnel into the new model of the 2.4 m wind tunnel, so that the new Mach number prediction could be conducted. Through simulation experiments, it was found that by introducing the NARX-BP algorithm to build the Mach number prediction model, the root-mean-square error (RMSE) of the model decreased by 44.93–77.90%, and the maximum deviation (MD) decreased by 64.05–85.32% compared to the BP model. The performance of the IOSBC-PSO migration model was also better than that of the non-migration model, as evidenced by the 82.06% decrease of the RMSE value and the 78.25% decrease of the MD value. The experiments showed the effectiveness of the proposed strategy.

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“…In the modeling of morphing aircraft, Seigler et al established a dynamic model of large-scale morphing flight for flight control problems and discussed various control methods [13]. Yang et al developed dynamic modeling and dynamic response analysis of the variable sweep and variable span aircraft and proved that the combination of a suitable variant mode and variant velocity can reduce the workload of the flight control system [14]. Yue et al analyzed the longitudinal multibody dynamics of the Z-wing morphing aircraft and showed that the variant of aerodynamic characteristics is the main factor affecting the dynamic characteristics of the aircraft during the folding process [15].…”

Section: Introductionmentioning

confidence: 99%

Integrated Guidance and Control for Hypersonic Morphing Missile Based on Variable Span Auxiliary Control

Bao

Wang

Tang

2019

International Journal of Aerospace Engineering

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The morphing aircraft can improve the flight performance of hypersonic vehicles by satisfying the flight requirements of large airspace and large velocity field. In this paper, for the hypersonic variable span missile, the dynamic model and aerodynamic model are established on the variable span characteristic. The adaptive dynamic surface control back-stepping method is used to establish the integrated guidance and control (IGC) with terminal angular constraint in the dive phase of the hypersonic variable span missile. The span variety is used to assist the lift control to achieve fast and stable control for the centroid motion. The simulation results demonstrate that the feasibility and robustness of the IGC method of the hypersonic variable span missile is better than the invariable span.

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Aerodynamic optimization of a morphing UAV with variable sweep and variable span

Cited by 6 publications

References 0 publications

Model and robust gain‐scheduled PID control of a bio‐inspired morphing UAV based on LPV method

Model and robust gain‐scheduled PID control of a bio‐inspired morphing UAV based on LPV method

Mach Number Prediction for 0.6 m and 2.4 m Continuous Transonic Wind Tunnels

Integrated Guidance and Control for Hypersonic Morphing Missile Based on Variable Span Auxiliary Control

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