Finite-Time Attitude Control With Chattering Suppression for Quadrotors Based on High-Order Extended State Observer

Chen, Hao; Shao, Xingling; Xu, Lexiu; Jia, Rong

doi:10.1109/access.2021.3128952

Cited by 8 publications

(4 citation statements)

References 34 publications

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“…V ≤ −κV + σ (34) where κ = min{2κ 1 , 2κ 2 ,} > 0, σ = k 2 δ 2 /2. Solving the inequality (34), one has…”

Section: Stability Analysismentioning

confidence: 99%

Section: Simulation Validation For Superioritymentioning

confidence: 99%

“…To illustrate the superiority of the evolved USDE in offering good estimation profiles, a constrastive investigation with a recently reported SMO [33] and a high-order extended state observer (HESO) [34] was carried out on the MATLAB/SIMULINK platform; it should be pointed that to govern the fairness of comparisons, for each estimator, the related design arguments were finely adjusted to assure the uniform convergence rate. Figure 6 gives the estimation errors between the USDE, and SMO [33], HESO [34]. Combined with the quantitative analysis collected in Table 3, significant jumping appeared in the SMO, which was incurred by using a weak sign function gain to reduce harmful chattering, and although HESO and the designed USDE shared similar estimation accuracy, intricate iterative operations were inevitably imposed on HESO, yielding a mass of calculational burden, while the USDE was capable of identifying the unmeasurable disturbances with a lessened computational consumption.…”

Section: Simulation Validation For Superioritymentioning

confidence: 99%

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Unknown System Dynamics Estimator-Based Anti-Disturbance Attitude Funnel Control for Quadrotors with Experimental Verifications

Zhen

Zhang

2022

Electronics

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In the article, an unknown system dynamics estimator-based anti-disturbance attitude funnel control technique is considered for quadrotors to ensure tracking performance when experiencing parametric uncertainties and external perturbations. To reinforce the anti-disturbance ability, an unknown system dynamics estimator was established by constructing the filtering operation-based invariant manifold, resulting in a more concise design framework, lower computational consumption and an asymptotic error convergence. Additionally, a funnel control policy was employed to regulate angle-tracking errors within a minor overshoot, a faster convergence time and a lower steady-state error by devising the funnel variables, where an exponential decaying function was used to construct the funnel boundary. The great improvements beyond the available quadrotor control policies are related to satisfied disturbance mitigation and performance guarantees as a priority despite uncertainties. The error arguments comprising of angle and angular rate for quadrotors were ultimately uniformly bounded and the angles controlling the deviations were restricted to the funnel boundary. Finally, the simulations and experiments verified the superiority of the proposed control technique in terms of reduced control actions and higher precision, as well as shorter settling time.

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“…V ≤ −κV + σ (34) where κ = min{2κ 1 , 2κ 2 ,} > 0, σ = k 2 δ 2 /2. Solving the inequality (34), one has…”

Section: Stability Analysismentioning

confidence: 99%

Section: Simulation Validation For Superioritymentioning

confidence: 99%

Section: Simulation Validation For Superioritymentioning

confidence: 99%

See 1 more Smart Citation

Unknown System Dynamics Estimator-Based Anti-Disturbance Attitude Funnel Control for Quadrotors with Experimental Verifications

Zhen

Zhang

2022

Electronics

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show abstract

“…Nonlinearity and unknown external disturbances are inherent in UAV systems. To enhance the robustness of proportional-integral-derivative control (PID) [1], several robust methods, such as intelligent control [2][3][4], fuzzy control [5][6][7], model predictive control [8], and sliding mode control (SMC) [9][10][11][12][13], have been proposed. Among them, SMC is a modelbased method with strong robustness to external disturbances and uncertainties, including equivalent control for realizing target tracking and switching control for suppressing nonlinear parts.…”

Section: Introductionmentioning

confidence: 99%

Chattering Reduction of Sliding Mode Control for Quadrotor UAVs Based on Reinforcement Learning

Wang

Namiki

Asignacion

et al. 2023

Drones

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Sliding mode control, an algorithm known for its stability and robustness, has been widely used in designing robot controllers. Such controllers inevitably exhibit chattering; numerous methods have been proposed to deal with this problem in the past decade. However, in most scenarios, ensuring that the specified form and the parameters selected are optimal for the system is challenging. In this work, the reinforcement-learning method is adopted to explore the optimal nonlinear function to reduce chattering. Based on a conventional reference model for sliding mode control, the network output directly participates in the controller calculation without any restrictions. Additionally, a two-step verification method is proposed, including simulation under input delay and external disturbance and actual experiments using a quadrotor. Two types of classic chattering reduction methods are implemented on the same basic controller for comparison. The experiment results indicate that the proposed method could effectively reduce chattering and exhibit better tracking performance.

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A review on quadrotor attitude control strategies

de Oliveira Evald,

Aoki,

da Silva

et al. 2024

Int J Intell Robot Appl

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Finite-Time Attitude Control With Chattering Suppression for Quadrotors Based on High-Order Extended State Observer

Abstract: Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Cited by 8 publications

References 34 publications

Unknown System Dynamics Estimator-Based Anti-Disturbance Attitude Funnel Control for Quadrotors with Experimental Verifications

Unknown System Dynamics Estimator-Based Anti-Disturbance Attitude Funnel Control for Quadrotors with Experimental Verifications

Chattering Reduction of Sliding Mode Control for Quadrotor UAVs Based on Reinforcement Learning

A review on quadrotor attitude control strategies

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