Experimental validation of quadrotor simulation tool for flight within building wakes

Raza, Syed Ali; Sutherland, M.; Etele, Jason; Fusina, Giovanni

doi:10.1016/j.ast.2017.03.043

Cited by 34 publications

(9 citation statements)

References 6 publications

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“…Precise attitude control of quadrotor is fundamental and necessary to complete tasks, which has become an important research hotspot (Zhao et al , 2019; Raza et al , 2017), and it is a challenging task how to design a controller robust to external disturbance, noise, wind and actual parameter changes (Roohul et al , 2016). A hybrid H2/H∞ static feedback tracking controller with measurement noise and external disturbance robustness is proposed, and the time response of mixed H2/H∞ controller is improved by increasing the regional pole assignment constraint (Emam and Fakharian, 2016).…”

Section: Introductionmentioning

confidence: 99%

Active disturbance rejection attitude control of unmanned quadrotor via paired coevolution pigeon-inspired optimization

Yuan¹,

Duan

2021

AEAT

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Purpose The purpose of this paper is to develop a novel active disturbance rejection attitude controller for quadrotors and propose a controller parameters identification approach to obtain better control results. Design/methodology/approach Aiming at the problem that quadrotor is susceptible to disturbance in outdoor flight, the improved active disturbance rejection control (IADRC) is applied to design attitude controller. To overcome the difficulty that adjusting the parameters of IADRC controller manually is complex, paired coevolution pigeon-inspired optimization (PCPIO) algorithm is used to optimize the control parameters. Findings The IADRC, where nonlinear state error feedback control law is replaced by non-singular fast terminal sliding mode control law and a third-order tracking differentiator is designed for second derivative of the state, has higher control accuracy and better robustness than ADRC. The improved PIO algorithm based on evolutionary mechanism, named PCPIO, is proposed. The optimal parameters of ADRC controller are found by PCPIO with the optimization criterion of integral of time-weighted absolute value of the error. The effectiveness of the proposed method is verified by a series of simulation experiments. Practical implications IADRC can improve the accuracy of attitude control of quadrotor and resist external interference more effectively. The proposed PCPIO algorithm can be easily applied to practice and can help the design of the quadrotor control system. Originality/value An improved active disturbance rejection controller is designed for quadrotor attitude control, and a hybrid model of PIO and evolution mechanism is proposed for parameters identification of the controller.

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Section: Introductionmentioning

confidence: 99%

Active disturbance rejection attitude control of unmanned quadrotor via paired coevolution pigeon-inspired optimization

Yuan¹,

Duan

2021

AEAT

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“…erefore, the development of a specialized controller, which is able to take into account the quadrotor's modeling nonlinearity with strongly coupled dynamics, underactuated characteristics, as well as parametric uncertainty, is always desired. Prior e ort has been put towards proportional-integral-derivative (PID) control [7][8][9], feedback linearization [10,11], active disturbance rejection control (ADRC) [12,13], model predictive control [14,15], internal model control [16], multivariable super-twisting-like-algorithm [17], backstepping control technique [18][19][20], etc.…”

Section: Introductionmentioning

confidence: 99%

Robust Tracking Control of a Quadrotor UAV Based on Adaptive Sliding Mode Controller

Huang

Wang

et al. 2019

Complexity

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In this paper, a robust adaptive sliding mode control scheme is developed for attitude and altitude tracking of a quadrotor unmanned aerial vehicle (UAV) system under the simultaneous effect of parametric uncertainties and consistent external disturbance. The underactuated dynamic model of the quadrotor UAV is first built via the Newton–Euler formalism. Considering the nonlinear and strongly coupled characteristics of the quadrotor, the controller is then designed using a sliding mode approach. Meanwhile, additional adaptive laws are proposed to further improve the robustness of the proposed control scheme against the parametric uncertainties of the system. It is proven that the control laws can eliminate the altitude and attitude tracking errors, which are guaranteed to converge to zero asymptotically, even under a strong external disturbance. Finally, numerical simulation and experimental tests are performed, respectively, to verify the effectiveness and robustness of the proposed controller, where its superiority to linear quadratic control and active disturbance rejection control has been demonstrated clearly.

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“…Recently, with the advancements in sensing technology, embedded computing devices, and information processing platforms, quadrotor aircraft has been widely applied in military and civil fields(–) such as small area monitoring, surveillance, detection in restricted terrains and reconnaissance, and aerial photography. Compared to fixed‐wing vehicles, the quadrotor has unique characteristics, eg, rapid maneuverability, precise hovering, and low‐cost manufacturability with reduced mechanical complexity.…”

Section: Introductionmentioning

confidence: 99%

Model‐assisted extended state observer and dynamic surface control–based trajectory tracking for quadrotors via output‐feedback mechanism

Shao

Liu

et al. 2018

Intl J Robust & Nonlinear

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Summary In this paper, an output‐feedback trajectory tracking controller for quadrotors is presented by integrating a model‐assisted extended state observer (ESO) with dynamic surface control. The quadrotor dynamics are described by translational and rotational loops with lumped disturbances to promote the hierarchical control design. Then, by exploiting the structural property of the quadrotor, a model information–assisted high‐order ESO that relies only on position measurements is designed to estimate not only the unmeasurable states but also the lumped disturbances in the rotational loop. In addition, to account for the problem of “explosion of complexity” inherent in hierarchical control, the output feedback–based trajectory tracking and attitude stabilization laws are respectively synthesized by utilizing dynamic surface control and the corresponding estimated signals provided by the ESO. The stability analysis is given, showing that the output‐feedback trajectory tracking controller can ensure the ultimate boundedness of all signals in the closed‐loop system and make the tracking errors arbitrarily small. Finally, flight simulations with respect to an 8‐shaped trajectory command are performed to verify the effectiveness of the proposed scheme in obtaining the stable and accurate trajectory tracking using position measurements only.

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Experimental validation of quadrotor simulation tool for flight within building wakes

Cited by 34 publications

References 6 publications

Active disturbance rejection attitude control of unmanned quadrotor via paired coevolution pigeon-inspired optimization

Active disturbance rejection attitude control of unmanned quadrotor via paired coevolution pigeon-inspired optimization

Robust Tracking Control of a Quadrotor UAV Based on Adaptive Sliding Mode Controller

Model‐assisted extended state observer and dynamic surface control–based trajectory tracking for quadrotors via output‐feedback mechanism

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