Design and flight-testing of non-linear formation control laws

Campa, Giampiero; Gu, Yu; Seanor, Brad; Napolitano, Marcello R.; Pollini, Lorenzo; Fravolini, Mario Luca

doi:10.1016/j.conengprac.2007.01.004

Cited by 90 publications

(64 citation statements)

References 20 publications

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“…The aerodynamic force vector can be defined as (cf. Campa et al (2007), Etkin (1972), Stengel (2004)…”

Section: Translational Kinematics and Dynamicsmentioning

confidence: 99%

“…Campa et al (2007), Etkin (1972), Stengel (2004), where x = V a α β , and where u = δ a δ e δ r is the control signal. The aerodynamic vector f (x) is defined as…”

Section: Rotational Kinematics and Dynamicsmentioning

confidence: 99%

“…The uav model that is employed is the YF-22 uav from Campa et al (2007) n axis, such that by defining q n,d = 1 0 0 0 , the objective is to perform a rotation of π radians such that the wind frame becomes aligned with the ned frame resulting in leveled flight. The desired angular velocity and acceleration are set equal to zero and the desired airspeed to V d = 40 m/s.…”

Section: Simulationmentioning

confidence: 99%

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A Decoupled Approach for Flight Control

Oland¹,

Kristiansen²

2016

MIC

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A decoupling method for flight control is presented that greatly simplifies the controller design. By approximating the higher order derivatives of the angle of attack and sideslip, it enables a rotation controller and a speed controller to be derived independently of each other, and thus gives access to a vast number of controller solutions derived for general classes of rotational and translational systems. For rotational control, a quaternion-based sliding surface controller is derived to align the wind frame in a desired direction, and using standard Lyapunov methods an airspeed controller is derived to ensure that an unmanned aerial vehicle moves with a positive airspeed. Simulations validate the potential of the proposed method, where the unmanned aerial vehicle is able to obtain leveled flight and move in a desired direction with a desired airspeed.

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“…The aerodynamic force vector can be defined as (cf. Campa et al (2007), Etkin (1972), Stengel (2004)…”

Section: Translational Kinematics and Dynamicsmentioning

confidence: 99%

“…Campa et al (2007), Etkin (1972), Stengel (2004), where x = V a α β , and where u = δ a δ e δ r is the control signal. The aerodynamic vector f (x) is defined as…”

Section: Rotational Kinematics and Dynamicsmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

See 1 more Smart Citation

A Decoupled Approach for Flight Control

Oland¹,

Kristiansen²

2016

MIC

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show abstract

“…Furthermore, three different approaches based on the state dependent Riccati equation, Sontag's formula and aggressive selection from a satisfying control set are proposed to design the heading and air speed control commands for this UAV [2]. The design of the formation control laws for YF-22 include inner and outer loop design for two aircraft in the formation -the outer loop scheme is based on feedback linearization, while the inner loop scheme is based on a root locus-based approach -and experimental results validate the performance [3]. The above methods improve the attitude and trajectory control performance of UAVs, however, the presented control methods are too complex to design and usually utilize a nonlinear model of a UAV.…”

Section: Introductionmentioning

confidence: 99%

UAV Flight Control System Based on an Intelligent BEL Algorithm

Huangzhong

Zhen

Jiang

et al. 2013

International Journal of Advanced Robotic Systems

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A novel intelligent control strategy based on a brain emotional learning (BEL) algorithm is investigated in the application of the attitude control of a small unmanned aerial vehicle (UAV) in this study. The BEL model imitates the emotional learning process in the amygdalaorbitofrontal (A-O) system of mammalian brains. Here it is used to develop the flight control system of the UAV. The control laws of elevator, aileron and rudder manipulators adopt the forms of traditional flight control laws, and three BEL models are used in above three control loops, to online regulate the control gains of each controller. Obviously, a BEL intelligent control system is self-learning and self-adaptive, which is important for UAVs when flight conditions change, while traditional flight control systems remain unchanged after design. In simulation, the UAV is on a flat flight and suddenly a wind disturbs it making it depart from the equilibrium state. In order to make the UAV recover to the original equilibrium state, the BEL intelligent control system is adopted. The simulation results illustrate that the BEL-based intelligent flight control system has characteristics of better adaptability and stronger robustness, when compared with the traditional flight control system.

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“…The leader and the follower in the formation flight proposed for simulation are WVU YF-22aircraft [18] and CONDOR Hybrid Electric Piloted Aircraft (HE-PRA) [19] respectively. Their geometrical and inertial data are given in Table-1 [18,19].The angle of attack of the follower at the level of altitude leader flight path, , is calculated as 0.5 a from the following values: leader velocity, 42y/2; atmospheric density at follower altitude, a 1.18|}/y~; atmospheric density at leader altitude, 1.21|}/y~; AOA of the follower at its original altitude, a 3 a .…”

Section: Simulationmentioning

confidence: 99%

Aerodynamic Stability Analysis of Two Heterogeneous UAVs in Close Formation Flight System

Johnson¹

2017

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Abstract:The close formation flight of UAVs has many significant advantages over single vehicle flight. The aerodynamic stability analysis of two heterogeneous UAVs in close formation flight is detailed in the present paper. The issues of altitude changes and the associated shifts or changes in centre of gravity or moments, the equivalent actuator control surface deflections etc. are explained with the help of simulations. The short period frequency variations with these changes are also correlated with the help of pole-zero diagrams.

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Design and flight-testing of non-linear formation control laws

Cited by 90 publications

References 20 publications

A Decoupled Approach for Flight Control

A Decoupled Approach for Flight Control

UAV Flight Control System Based on an Intelligent BEL Algorithm

Aerodynamic Stability Analysis of Two Heterogeneous UAVs in Close Formation Flight System

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