Globally Stable Attitude Control of a Fixed-Wing Rudderless UAV Using Subspace Projection

Mitikiri, Yujendra; Mohseni, Kamran

doi:10.1109/lra.2019.2895889

Cited by 6 publications

(5 citation statements)

References 19 publications

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“…The existing work in the literature that shares the most similarities with this paper can be found in [58][59][60][61], where nonlinear attitude controllers for fixed-wing UAVs are devel-oped using quaternions, and that also use a model of the rotational dynamics. In [58,59], the translational and rotational subsystems are decoupled by estimating the higher-order derivatives of the angle of attack and sideslip angle.…”

Section: Related Workmentioning

confidence: 99%

“…The control law is based on unit quaternions and compensates for aerodynamic coupling effects using integral action. This approach is extended in [61] to apply also to rudderless (i.e., underactuated in attitude) fixed-wing UAVs by using a projection of the quaternion error to a yaw-free subspace. In [62], a gainscheduled attitude controller based on Euler angles is given.…”

Section: Related Workmentioning

confidence: 99%

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Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Coates

Fossen

2021

Applied Sciences

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This paper presents nonlinear, singularity-free autopilot designs for multivariable reduced-attitude control of fixed-wing aircraft. To control roll and pitch angles, we employ vector coordinates constrained to the unit two-sphere and that are independent of the yaw/heading angle. The angular velocity projected onto this vector is enforced to satisfy the coordinated-turn equation. We exploit model structure in the design and prove almost global asymptotic stability using Lyapunov-based tools. Slowly-varying aerodynamic disturbances are compensated for using adaptive backstepping. To emphasize the practical application of our result, we also establish the ultimate boundedness of the solutions under a simplified controller that only depends on rough estimates of the control-effectiveness matrix. The controller design can be used with state-of-the-art guidance systems for fixed-wing unmanned aerial vehicles (UAVs) and is implemented in the open-source autopilot ArduPilot for validation through realistic software-in-the-loop (SITL) simulations.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Coates

Fossen

2021

Applied Sciences

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“…is chapter establishes a mathematical model of a fixedwing UAV based on the body coordinate system. e position and attitude kinematics models of the fixed-wing UAV can be obtained through the transformation relationship between different coordinate systems [30,31] as follows: Ψ is the yaw angle, θ is the pitch angle, and Φ is the roll angle.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…where F is the accumulation of external forces, m is the mass of the UAV, M is the accumulation of torques, and H is the angular momentum. Expand these two formulas according to the force conditions to obtain the dynamic model related to the displacement acceleration and angular acceleration of the fixed-wing UAV [31]:…”

Section: Mathematical Modelmentioning

confidence: 99%

Design of a Fixed-Wing UAV Controller Combined Fuzzy Adaptive Method and Sliding Mode Control

Guo

Luo

Bao

2022

Mathematical Problems in Engineering

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To overcome the complexity of the coupled nonlinear model of a fixed-wing UAV system and the uncertainty caused by a large number of interference factors, a control algorithm combining fuzzy adaptive control and sliding mode variable structure control was proposed. The controller algorithm mainly relies on the sliding mode variable structure control method to solve the control problem of the strongly coupled complex nonlinear system. Based on sliding mode control, a fuzzy adaptive method is introduced to reduce the chattering problem of the traditional sliding mode control, and the uncertain parameters and unknown functions caused by external disturbances are approximated by this method. In this study, two types of fuzzy adaptive sliding mode controller were designed according to the different object ranges of the fuzzy adaptive algorithm. In addition, the stability of the controllers was verified using the Lyapunov method. Finally, numerical simulations are performed to demonstrate the effectiveness of the proposed controllers by comparing with the traditional sliding mode controller.

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“…Consider the Lyapunov candidate function (17). Applying control input (23) and adaptive law (25), the time derivative of V is calculated as…”

Section: 2mentioning

confidence: 99%

Robust adaptive sliding mode tracking control for a rigid body based on Lie subgroups of SO(3)

Ye¹,

Basin²

2022

DCDS-S

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<p style='text-indent:20px;'>This paper considers the attitude tracking control problem for a rigid body. In order to avoid the complexity and ambiguity associated with other attitude representations (such as Euler angles or quaternions), the attitude dynamics and the proposed control system are represented globally on special orthogonal groups. An adaptive controller based on a Lie subgroup of SO(3) is developed such that the rigid body can track any given attitude command asymptotically without requiring the exact knowledge of the inertia moment. In the presence of external disturbances, the adaptive controller is enhanced with an additional robust sliding mode term by following the same idea within the framework of SO(3). Finally, simulation results are presented to demonstrate efficiency of the proposed controllers.</p>

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Globally Stable Attitude Control of a Fixed-Wing Rudderless UAV Using Subspace Projection

Cited by 6 publications

References 19 publications

Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Geometric Reduced-Attitude Control of Fixed-Wing UAVs

Design of a Fixed-Wing UAV Controller Combined Fuzzy Adaptive Method and Sliding Mode Control

Robust adaptive sliding mode tracking control for a rigid body based on Lie subgroups of SO(3)

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