Transient Dynamic Analysis and Control of a Morphing UAV

Prabhakar, Nirmit; Prazenica, Richard J.; Gudmundsson, Snorri; Balas, Mark J.

doi:10.2514/6.2016-0893

Cited by 10 publications

(8 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, they used a backstepping control method to design a four-rotor controller, and achieved better simulation results. In addition, special tools, e.g., MATLAB/Simulink [5], have also contributed much to this field.…”

Section: Introductionmentioning

confidence: 99%

Simulating unmanned aerial vehicle flight control and collision detection

Liu

Gai

Lai

2019

Vis. Comput. Ind. Biomed. Art

View full text Add to dashboard Cite

An unmanned aerial vehicle (UAV) is a small, fast aircraft with many useful features. It is widely used in military reconnaissance, aerial photography, searches, and other fields; it also has very good practical-application and development prospects. Since the UAV's flight orientation is easily changeable, its orientation and flight path are difficult to control, leading to its high damage rate. Therefore, UAV flight-control technology has become the focus of attention. This study focuses on simulating a UAV's flight and orientation control, and detecting collisions between a UAV and objects in a complex virtual environment. The proportional-integral-derivative control algorithm is used to control the orientation and position of the UAV in a virtual environment. A version of the bounding-box method that combines a grid with a k-dimensional tree is adopted in this paper, to improve the system performance and accelerate the collision-detection process. This provides a practical method for future studies on UAV flight position and orientation control, collision detection, etc.

show abstract

Section: Introductionmentioning

confidence: 99%

Simulating unmanned aerial vehicle flight control and collision detection

Liu

Gai

Lai

2019

Vis. Comput. Ind. Biomed. Art

View full text Add to dashboard Cite

show abstract

“…In this paper, Datcom is employed to calculate these derivatives for the aircraft when symmetric planform changes are implemented for that we focus on the longitudinal altitude controller design. To reduce the difficulties in calculating aerodynamic parameters at the basis of guarantee accuracy, the following assumptions are made which are commonly used [1,15]:…”

Section: Aerodynamic Parametersmentioning

confidence: 99%

“…ability to optimize flight in different conditions via altering shape [1], possess the remarkable performance, e.g. flight in multiple mission types and extreme maneuver performance, of which is not possible for a traditional fixed-wing aircraft [2,3].…”

mentioning

confidence: 99%

Nonlinear robust adaptive NN control for variable-sweep aircraft

Ma¹,

Feng²,

Hu³

et al. 2018

J. vibroeng.

View full text Add to dashboard Cite

In this paper, we address the problem of altitude and velocity controllers design for variable-sweep aircraft with model uncertainties. The object is to maintain altitude and velocity during the wing transition process where mass distribution and aerodynamic parameters change significantly. Based on the functional decomposition, the longitudinal dynamics of the aircraft can be divided into altitude subsystem in non-affine pure feedback form and velocity subsystem. And then nonlinear robust adaptive NN velocity controller and altitude controller are designed with backstepping method to relax the prior requirements of aerodynamic parameters accuracy in linear LPV controller design. The method of filtered signal is used to circumvent the algebraic loop problem caused by the dynamics of non-affine pure feedback form. Dynamic surface control (DSC) and minimal learning parameters (MLP) techniques are employed to solve the problems of 'explosion of complexity' in the back-stepping method and the online updated parameters being too much. The robust terms have been introduced to eliminate the influences of approximation errors. According to the Lyapunov-LaSalle invariant set theorem, the semi-global boundedness and convergence of all the signals of the closed-loop system are proved. Simulation results are presented to illustrate the control algorithm with good performance.

show abstract

“…Such obstacles are a great challenge for modeling and control design. Current research on flight control of MUAVs mainly focuses on control of static states , which treats the morphing UAV as a statically configured one, even in the morphing process. This is a great simplification of the dynamics in the morphing process but cannot work well in some practical cases because the parameter variation is ignored.…”

Section: Introductionmentioning

confidence: 99%

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

View full text Add to dashboard Cite

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.

show abstract

Transient Dynamic Analysis and Control of a Morphing UAV

Cited by 10 publications

References 5 publications

Simulating unmanned aerial vehicle flight control and collision detection

Simulating unmanned aerial vehicle flight control and collision detection

Nonlinear robust adaptive NN control for variable-sweep aircraft

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

Contact Info

Product

Resources

About