Generalized Extended State Observer Based High Precision Attitude Control of Quadrotor Vehicles Subject to Wind Disturbance

Shi, Di; Wu, Zhong; Chou, Wu

doi:10.1109/access.2018.2842198

Cited by 65 publications

(43 citation statements)

References 39 publications

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“…In order to verify the enhancement of STESO relative to traditional Higher-order ESO, three comparative simulations are conducted on condition that use nonlinear PD controller as the FC. The controller gains are chosen as K 1 = I 3 and K 2 = 5I 3 [44], the observer gains of STESO are chosen as a i = 24 and b i = 50, and the bandwidth of 2nd-order ESO is chosen as 10 rad/s, i.e., the observer gains are L = [ 30 300 1000 ] T [45]. Figures 3-5 show the comparison in attitude tracking results of nonlinear PD controller with STESO, 2nd-order ESO and without DUE.…”

Section: Simulation Resultsmentioning

confidence: 99%

Super-Twisting Extended State Observer and Sliding Mode Controller for Quadrotor UAV Attitude System in Presence of Wind Gust and Actuator Faults

Shi

Chou

2018

Electronics

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This article addresses the problem of high precision attitude control for quadrotor unmanned aerial vehicle in presence of wind gust and actuator faults. We consider the effect of those factors as lumped disturbances, and in order to realize the quickly and accurately estimation of the disturbances, we propose a control strategy based on the online disturbance uncertainty estimation and attenuation method. Firstly, an enhanced extended state observer (ESO) is constructed based on the super-twisting (ST) algorithm to estimate and attenuate the impact of wind gust and actuator faults in finite time. And the convergence analysis and parameter selection rule of STESO are given following. Secondly, in order to guarantee the asymptotic convergence of desired attitude timely, a sliding mode control law is derived based on the super-twisting algorithm. And a comprehensive stability analysis for the entire system is presented based on the Lyapunov stability theory. Finally, to demonstrate the efficiency of the proposed solution, numerical simulations and real time experiments are carried out in presences of wind disturbance and actuator faults.

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Section: Simulation Resultsmentioning

confidence: 99%

Super-Twisting Extended State Observer and Sliding Mode Controller for Quadrotor UAV Attitude System in Presence of Wind Gust and Actuator Faults

Shi

Chou

2018

Electronics

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“…Therefore, special attention needs to be taken during the vertical motion control design process. Furthermore, from Figure 4 it is observed the smoothly transients of the position regulation of the yaw angle by using the polynomial (24), such that the computed yawing torque is sufficiently soft and free of high frequency oscillations. On the other hand, Figure 5 shows that the proposed adaptive control configuration allows the system performing an effective tracking of the pitch and roll angles (computed on-line by expression (10)) in spite of the fact that derivativesφ * andθ * are not included in the control scheme.…”

Section: Nominal Adaptive Control Performancementioning

confidence: 90%

“…In this section the Dryden wind gust model presented in [24] is introduced to the system in order to verify the quadrotor behaviour by using the proposed controller. Here, it is assumed that the disturbance caused by wind field is proportional to the wind speed, and is defined as a set of sinusoidal excitations given by…”

Section: Dynamic Response In Presence Of Turbulent Wind Fieldmentioning

confidence: 99%

“…One fact that should be pointed out is that many uncertainties in control systems are unmeasurable; thus, the disturbance estimation technique represents a very good alternative to actively suppress time-varying disturbances [19,20]. Effectiveness and robustness of the ADRC has been proved for a wide range of engineering applications which involve different single input-output (SISO) and and multiple input -output (MIMO) systems (e.g., power converters [21], electric motor drives [22], mechanical systems [23], unmanned aerial vehicles [24], among others).…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Neural Motion Control of a Quadrotor UAV

Yañez-Badillo¹,

Tapia‐Olvera

Beltrán-Carbajal

2020

Vehicles

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Unmanned Aerial Vehicles have generated considerable interest in different research fields. The motion control problem is among the most important issues to be solved since system dynamic stability depends on the robustness of the main controller against endogenous and exogenous disturbances. In spite of different controllers have been introduced in the literature for motion control of fixed and rotary wing vehicles, there are some challenges for improving controller features such as simplicity, robustness, efficiency, adaptability, and stability. This paper outlines a novel approach to deal with the induced effects of external disturbances affecting the flight of a quadrotor unmanned aerial vehicle. The aim of our study is to further extend the current knowledge of quadrotor motion control by using both adaptive and robust control strategies. A new adaptive neural trajectory tracking control strategy based on B-spline artificial neural networks and on-line disturbance estimation for a quadrotor is proposed. A linear extended state observer is used for estimating time-varying disturbances affecting the controlled nonlinear system dynamics. B-spline artificial neural networks are properly synthesized for on-line calculating control gains of an adaptive Proportional Integral Derivative (PID) scheme. Simulation results highlight the implementation of such a controller is able to reject disturbances meanwhile perform proper motion control by exploiting the robustness, disturbance rejection, adaptability, and self-learning capabilities.

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“…In one study a wind disturbance estimator was used in quadrotor control to reject wind disturbance based on the wind model, in which measurement of wind velocity is needed to estimate the disturbance [21]. In another study, a generalized extend state observer (GESO)-based disturbance estimator is used in the quadrotor attitude wind disturbance reject control, in which the disturbance is considered as a time polynomial function [22]. In a third study, a disturbance observer (DOB)-based method was used in quadrotor position control to reject the external force disturbance, in which the disturbance was estimated by the disturbance observer [23].…”

Section: Introductionmentioning

confidence: 99%

Aerial Grasping of an Object in the Strong Wind: Robust Control of an Aerial Manipulator

Zhang

Dai

et al. 2019

Applied Sciences

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An aerial manipulator is a new kind of flying robot system composed of a rotorcraft unmanned aerial vehicle (UAV) and a multi-link robotic arm. It gives the flying robot the capacity to complete manipulation tasks. Steady flight is essential for an aerial manipulator to complete manipulation tasks. This paper focuses on the steady flight control performance of the aerial manipulator. A separate control strategy is used in the aerial manipulator system, in which the UAV and the manipulator are controlled separately. In order to complete tasks in environments with strong wind disturbance, an acceleration feedback enhanced robust H∞ controller was designed for the UAV in the aerial manipulator. The controller is based on the hierarchical inner-outer loop control structure of the UAV and composed of a robust H∞ controller and acceleration feedback enhanced term, which is used to compensate for the wind disturbance. Experimental results of aerial grasping of a target object show that the controller can suppress the wind disturbance effectively, and make the aerial manipulator hover steadily with sufficient accuracy to complete aerial manipulation tasks in strong wind.

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Generalized Extended State Observer Based High Precision Attitude Control of Quadrotor Vehicles Subject to Wind Disturbance

Cited by 65 publications

References 39 publications

Super-Twisting Extended State Observer and Sliding Mode Controller for Quadrotor UAV Attitude System in Presence of Wind Gust and Actuator Faults

Super-Twisting Extended State Observer and Sliding Mode Controller for Quadrotor UAV Attitude System in Presence of Wind Gust and Actuator Faults

Adaptive Neural Motion Control of a Quadrotor UAV

Aerial Grasping of an Object in the Strong Wind: Robust Control of an Aerial Manipulator

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