Airship Hover Stabilization Using a Backstepping Control Approach

Azinheira, José Raul; Moutinho, Alexandra; Paiva, Ely C. de

doi:10.2514/1.17334

Cited by 67 publications

(47 citation statements)

References 13 publications

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“…As assumed previously, the wind input is not affecting the angular position part in (7), and therefore only the cartesian position p of the airship should be considereḋ…”

Section: Appendix A: Wind Estimatormentioning

confidence: 99%

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A backstepping controller for path‐tracking of an underactuated autonomous airship

Azinheira¹,

Moutinho²,

Paiva³

2008

Intl J Robust & Nonlinear

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SUMMARYIn this paper we propose a nonlinear control approach for the path-tracking of an autonomous underactuated airship. A backstepping controller is designed from the airship nonlinear dynamic model including wind disturbances, and further enhanced to consider actuators saturation. Control implementation issues related to airship underactuation are also addressed, namely control allocation and an attitude reference shaping to obtain a faster error correction with smoother input requests. The results obtained demonstrate the capacity of an underactuated unmanned airship to execute a realistic mission including vertical take-off and landing, stabilization and path-tracking, in the presence of wind disturbances, with a single robust control law.

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“…As assumed previously, the wind input is not affecting the angular position part in (7), and therefore only the cartesian position p of the airship should be considereḋ…”

Section: Appendix A: Wind Estimatormentioning

confidence: 99%

“…For the derivation of the kinematics equations (10a)-(10b) and the definition of matrix 7 ∈ R 7×7 , see Reference [7].…”

mentioning

confidence: 99%

A backstepping controller for path‐tracking of an underactuated autonomous airship

Azinheira¹,

Moutinho²,

Paiva³

2008

Intl J Robust & Nonlinear

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“…To account for the coupling of translational and rotational motion, equation (5) will be used to transform ξ D and a D into the desired net forces and moments acting on the airship. These can then be used in equations (6), and (7) to calculate the desired thruster forces f T and moments n T .…”

Section: Controller Designmentioning

confidence: 99%

“…These calculations are based on equations (5), (6), and (7). However, this raises one last issue that needs to be resolved first.…”

Section: Calculation Of the Desired Thruster Forces And Momentsmentioning

confidence: 99%

Integral backstepping control of an unmanned, unstable, fin-less airship

Liesk

2010

AIAA Guidance, Navigation, and Control Conference

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This paper discusses the design of a combined backstepping/Lyapunov controller for the attitude and velocity control of an unmanned, unstable, fin-less airship. The controller includes a quadratic optimization algorithm to find the optimal thruster commands, as the airship actuation has more degrees of freedom than the motion controlled. The paper also describes the setup of a simulation to validate the controller performance including detailed modeling of sensor noise, computational delays and actuation dynamics. Using this simulation, the controller performance is validated for two different wind conditions, and compared to the performance of a simple PID controller. The controller is found to perform well in both wind conditions and to exhibit a better tracking performance than the PID-controller.Nomenclature a x,D , a z,D Desired acceleration along body x-axis and z-axisVector from the airship's center of buoyancy to the center of gravity [ c x c y c z ] T c ij Tuning parameters of the attitude controller (i = a) and the velocity controller (i = v) C × ∈ R 3×3 Matrix representing the cross product c× f , f T , f V Sum of forces vector, thruster forces vector, viscous forces vector F i Thrust force of the i-th thruster g Gravitational acceleration hDiscrete sampling timeTotal mass of the airship (including mass of the lifting gas) m D Mass of the air displaced by the airship M a ∈ R 3×3 Apparent mass matrix (M a = mI + A m ) with the diagonal entries m ax , m ay , m az M a ∈ R 6×6 Generalized apparent mass matrixdiagonal entries m Dax , m Day , m Daz n, n T , n V Sum of moments vector, thruster moments vector, viscous moments vector q Attitude quaternion [ q 0 q 1 q 2 q 3 ] T Q ω ∈ R 4×3 Matrix to transform the angular rate vector to the quaternion derivative R ∈ R 3×3 Direction cosine matrix r b Position vector of the body frame origin/center of buoyancy [ r b,n r b,e r b,d ] T r T i Position vector of the i-th thruster [ r T i,x r T i,y r T i,z ] T v Airship inertial velocity vector [ u v w ] T v a , v w Airship airspeed vector, wind velocity vector V Volume of the airship hull V i Control Lyapunov function (for i=1,2,v)

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“…However, these controllers are based on the approximation-linearized model of airships, and they are efficient only around the equilibrium state. Furthermore, dynamic inversion technology [13,14] and backstepping technology [15,16] have been applied to the autonomous airship based on its nonlinear model. In addition to stabilization control, the trajectory tracking [17,18] and pathfollowing control [19] driving the position of airship to a desired time-varying trajectory should be studied, and the airship can be controlled to perform the cruising flight [20][21][22] and station-keeping tasks [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear adaptive trajectory tracking control for a stratospheric airship with parametric uncertainty

Sun

Zheng

2015

Nonlinear Dyn

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A nonlinear adaptive trajectory tracking control strategy is proposed for a fully actuated stratospheric airship subject to uncertain mass and inertia parameters. Based on the stratospheric airship trajectory tracking model, a non-certainty equivalence adaptive control approach is adopted to estimate the uncertain parameters since its excellently attractive property of the immersion and invariance manifold condition.The key idea involves a new filter construction for the regressor terms in the airship dynamics that enables the establishment of a stabilizing mechanism within the adaption process for uncertain parameters. It is proved that trajectory tracking errors asymptotically converge to zero within the Lyapunov framework. Numerical simulations are presented to demonstrate the performance of the proposed controller.

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Airship Hover Stabilization Using a Backstepping Control Approach

Cited by 67 publications

References 13 publications

A backstepping controller for path‐tracking of an underactuated autonomous airship

A backstepping controller for path‐tracking of an underactuated autonomous airship

Integral backstepping control of an unmanned, unstable, fin-less airship

Nonlinear adaptive trajectory tracking control for a stratospheric airship with parametric uncertainty

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