Control of a Quadrotor Vehicle Using Sliding Mode Disturbance Observer

Besnard, Lénaïck; Shtessel, Yuri B.; Landrum, Brian

doi:10.2514/6.2007-6316

Cited by 32 publications

(35 citation statements)

References 6 publications

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“…To deal with this system, many modeling approaches have been presented [1,2] and various control methods proposed [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. First of all, several backstepping controllers have been developed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

Lee

Kim

Sastry

2009

Int. J. Control Autom. Syst.

605

295

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This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects.

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Section: Introductionmentioning

confidence: 99%

“…A sliding mode disturbance observer was presented in [13] to design a robust flight controller for a quadrotor vehicle. This controller allowed continuous control robust to external disturbance, model uncertainties and actuator failure.…”

Section: Introductionmentioning

confidence: 99%

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

Lee

Kim

Sastry

2009

Int. J. Control Autom. Syst.

605

295

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“…Recently, Bonnabel, Martin, and Rouchon (2006), Vik and Fossen (2001), Zhao and Slotine (2005), Benallegue et al (2008), Besnard et al (2007), Boutayeb et al (2008), Benzemrane et al (2007), Benzemrane (2009), Madani and Benallegue (2007) and Pflimlin et al (2007) have proposed observers to be implemented on UAVs. The critical issue in this domain comes from the fact that the translation velocity is classically known as non-observable.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear speed estimation of a GPS-free UAV

Santosuosso¹,

Benzemrane²,

Damm³

2011

International Journal of Control

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International audienceIn this article, the problem of robust state observer design for a class of unmanned aerial vehicles (UAVs) is addressed. A prototype four-rotors helicopter robot for indoors and outdoors applications is considered: the drone is not equipped with GPS related devices, so we describe a strategy to estimate its translational velocity vector based on acceleration, angles and angular speeds measurements only. Since the linearised system is non-observable at the equilibrium point, a nonlinear observability verification is performed for persistently exciting trajectories. A global exponential solution to this open problem is provided in the framework of adaptive observation theory when exact measurements are available. A modified observer is presented to enhance velocity estimation robustness in the realistic case of noisy measurements. The results are compared with a classical estimation strategy based on the extended Kalman filter to test the algorithm's performance

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“…Briefly, they proposed several control approaches based on Riccati equations, sliding mode technique, robust adaptive-fuzzy technique, and full state backstepping technique. In addition to these works, some papers were published in 2007: Besnard et al (2007) developed a sliding mode disturbance observer to control a quadrotor; Erginer and Altuğ (2007) implemented a PD control and Benallegue (2007-a and2007-b) proposed a backstepping control and a sliding mode observer for quadrotors; and Voos (2007) used a control system based on a combination of state-dependent Riccati equations and neural networks to control the quadrotors attitude and velocity.…”

Section: Quadrotorsmentioning

confidence: 99%