Experimental results on adaptive output feedback control using a laboratory model helicopter

Kutay, Ali Türker; Calise, Anthony J.; Idan, Moshe; Hovakimyan, Naira

doi:10.1109/tcst.2004.839563

Cited by 99 publications

(22 citation statements)

References 11 publications

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“…1): θ(t) -pitch angle; 4 ε(t) -elevation angle; λ(t) -travel angle; v f (t), v r (t) -control voltages of the "front" (conditionally) and the "rear" motors; u(t) -pitch torque command 2 http://www.quanser.com/choice.asp 3 LAAS-CNRS, http://www.laas.fr 4 In the present paper the manufacturer's system of notation [18] is used: the turning angle of the "Helicopter body" about the long arm is called the pitch angle θ; the pitch angle of the paper [9] is known here as the elevation angle ε. signal w(t) -normal force command signal (used for elevation/travel control); f f (t), f r (t) -tractive forces of the "front" and "rear" propellers, N.…”

Section: B Nomenclaturementioning

confidence: 99%

Adaptive Identification of Angular Motion Model Parameters for LAAS Helicopter Benchmark

Peaucelle

Fradkov

Andrievsky

2007

2007 IEEE International Conference on Control Applications

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The paper is devoted to design and experimental testing the adaptive identification algorithms of pitch and elevation model parameters for "LAAS Helicopter Benchmark". The adaptive identification algorithms for separate pitch and elevation motions are proposed and the experimental results are presented. Laboratory experiments clarify the properties of the adaptive identification algorithms in real-world conditions.

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Section: B Nomenclaturementioning

confidence: 99%

Adaptive Identification of Angular Motion Model Parameters for LAAS Helicopter Benchmark

Peaucelle

Fradkov

Andrievsky

2007

2007 IEEE International Conference on Control Applications

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“…For Quanser table-mount helicopter platform, past works show that state-feedback methods can achieve good dynamic and static performances even in aggressive maneuvers [17], while experimental results on output-feedback approaches are very limited. Kutay et al [21] gave the first experimental results of an adaptive output feedback approach for pitch axis only of the platform, but the coupling and high nonlinearity in multi-axis cases were not discussed. Rosales et al [20] presented results for three axes control but only set-point regulation problem was considered and the performance was limited.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Robust Attitude Tracking Control of a Table-Mount Experimental Helicopter Using Output Feedback

Liu

Zhu

et al. 2015

IEEE Trans. Ind. Electron.

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This work proposes a robust attitude tracking controller for a table-mounted experimental helicopter which has three rotational degree-of-freedom and only equips angular position sensors. The proposed controller can achieve outputfeedback attitude tracking of the pitch and elevation channels of the helicopter. The experimental platform is subjected to model uncertainties, coupling effects, and equips with an independent active disturbance system, which have effectively examined the robustness of proposed controller. The control law includes a second-order auxiliary system to generate filtered error signals, and a discontinuous uncertainty and disturbance estimation (UDE) term to compensate the model uncertainties and external disturbances. A Lyapunov based stability analysis shows the semiglobal asymptotic tracking ability of the proposed controller. The experimental results further demonstrate the propose method can achieve equivalent dynamic and static performance compare to other high-performance state-feedback methods, and even when the initial position is away from design point, it also gives more consistent responses than other linear methods.

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“…The advantages of this experimental system, the 3DOF Quanser helicopter [1], are its reasonable small size, which allows to test some control laws with a high level of safety, and the possibility to evaluate advanced attitude controllers versus perturbations (thanks to the use of domestic fans). Without being exhaustive, the following list of previously published results [2][3][4][5][6][7] shows that many works have been made for the design of linear/nonlinear attitude controllers. Note that all these works have made some hypothesis on the structural properties of the system (for example, controllers based on singular perturbation theory [8][9][10]); on the mechanical architecture, however, all these assumptions highly reduce the realism of the simulations.…”

Section: Introductionmentioning

confidence: 99%

Adaptive robust attitude control for UAVs – Design and experimental validation

Chriette

Plestan

Castañeda

et al. 2015

Adaptive Control & Signal

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The main contribution of the paper is to propose a scheme of attitude controller for a class of unmanned aerial vehicles based on an adaptive version of the super-twisting algorithm. This controller is based on a very recent second-order sliding mode controller, which is robust in spite of uncertainties and perturbations, ensures finite time convergence, reduces the chattering, increases the accuracy, and does not require time derivative of the sliding variable. A very important feature of the controller is its adaptive gain, which allows to design the controller without knowing bounds of the uncertainties and perturbations. This controller is validated by experimental results. Comparisons versus PID-based controller are made in order to evaluate the robustness of the closed-loop system when similar perturbations are acting. 1479has been initially developed in [11] and used in [12, 13]: it allows to decouple the system thanks to the introduction of both virtual inputs for travel and elevation angles and to design a desired reference for the pitch angle. This approach is adapted to user's expectations. Indeed, in standard working conditions, the user can provide elevation and travel desired trajectories with respect to his objective, the pitch trajectory being online defined to achieve the tracking of elevation/travel desired trajectories. The controller scheme used in [11][12][13] has been modified in the current paper in order to prove the stability of the closed-loop system (which has not been formally established in the previous papers). The proposed controller is based on adaptive second-order sliding mode, which allows to obtain robust behavior with respect to modeling errors, uncertainties, and perturbations, while having reduced magnitude gain, which is dynamically adapted. It is well known that sliding mode control is robust with respect to perturbations and uncertainties and is simple to be tuned (high gain approach by considering the 'worst' case). Unfortunately, high frequency oscillations of the control input, the so-called chattering phenomenon, appear and can damage the actuators. In order to reduce this phenomenon, to improve the accuracy, and to ensure finite time convergence to the control objective, high-order sliding mode control appears at the beginning of 1990s [14], especially second-order sliding mode controllers as twisting and super-twisting (STW) algorithms. The advantage of the STW algorithm versus the twisting one is that no time derivative of the sliding variable is required, which reduces the noise in the control input. In the current paper, an adaptive version of the STW controller is used [15,16]. This adaptive algorithm allows a robust control without overestimating the control gains for a large class of nonlinear systems of relative degree 1 with bounded additive and multiplicative uncertainties perturbations whose bounds are unknown. Note that this latter feature is interesting given that it allows to reduce the identification procedure.The controller proposed in the sequel is, ...

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Experimental results on adaptive output feedback control using a laboratory model helicopter

Cited by 99 publications

References 11 publications

Adaptive Identification of Angular Motion Model Parameters for LAAS Helicopter Benchmark

Adaptive Identification of Angular Motion Model Parameters for LAAS Helicopter Benchmark

Nonlinear Robust Attitude Tracking Control of a Table-Mount Experimental Helicopter Using Output Feedback

Adaptive robust attitude control for UAVs – Design and experimental validation

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