Neuro-adaptive singularity-free finite-time attitude tracking control of quadrotor UAVs

He, Xiongxiong; Tao, Meiling; Xie, Shuzong; Chen, Qiang

doi:10.1016/j.compeleceng.2021.107485

Cited by 6 publications

(2 citation statements)

References 21 publications

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“…As the inner loop of the cascaded control structure, the attitude control loop plays a pivotal role in improving control quality, rapidly responding to internal system changes, and addressing the impact of disturbances on the system's main parameters. In recent years, advanced control techniques such as high-order sliding mode control [4], neural network adaptive control [5], and the linear quadratic regulator integrated with interval analysis techniques [6,7] have been employed to tackle control issues arising from uncertainties and external disturbances in the attitude control systems of quadrotors or satellites. However, the above control methods also have significant limitations such as the need for high accuracy in system modeling, numerous controller parameters tuning, and complex mathematical computations.…”

Section: Introductionmentioning

confidence: 99%

Quadrotor attitude control by improved snake optimizer based adaptive switching disturbance rejection approach

Zhou,

Chen,

Jiao

2024

Meas. Sci. Technol.

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In this paper, an adaptive switching anti-disturbance attitude control scheme based on improved snake optimizer is proposed for quadrotor attitude control when a quadrotor unmanned aerial vehicle is affected by measurement noise. The adaptive switching disturbance rejection controller (AWDRC) is composed of linear active disturbance rejection control and adaptive switching extended state observer which is used to achieve accurate signals reconstruction performance under measurement noise. Then, the improved snake optimizer (ISO) algorithm is developed with quadratic interpolation and comprehensive learning strategies to obtain the optimal parameters of the quadrotor attitude controller. The performance validity of ISO is demonstrated here by experiments on the CEC-2017 and the CEC-2020 benchmark functions with several state-of-the-art meta-heuristic algorithms. Secondly, the proposed ISO-based AWDRC algorithm is used in quadrotor attitude tracking control and compared with three other excellent active disturbance rejection controllers in a comparative experiment, and the experimental results show the effectiveness of the proposal. Finally, the robustness of the proposed method to parameters perturbation of the quadrotor attitude system is analyzed by Monte Carlo experiments.

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Section: Introductionmentioning

confidence: 99%

Quadrotor attitude control by improved snake optimizer based adaptive switching disturbance rejection approach

Zhou,

Chen,

Jiao

2024

Meas. Sci. Technol.

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“…On the other hand, it should be pointed out that intelligent technology which has a strong nonlinear approximation capability has also been treated as an effective anti-perturbation method in the control field. Recently, neural network-based intelligent control schemes have been greatly enriched, which focus on multi-agent systems, 25,26 robot manipulators, 27,28 intelligent flight control, 29,30 robotic systems 31,32 and so on. It is obvious that combined with adaptive, sliding mode, and neural network techniques, the robustness of systems shall be largely improved for application.…”

Section: Introductionmentioning

confidence: 99%

Fixed‐time linear quadratic adaptive sliding mode control for a class of cart‐pendulum robots

Jin

Liu

et al. 2022

Optim Control Appl Methods

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This article is concerned with the fixed-time path-following control problem of a perturbed cart-pendulum robot with linear quadratic (LQ) performance optimization. In order to ensure the displacements of cart and pendulum of the robot following the desired paths within fixed-time, adaptive anti-perturbation sliding mode control schemes with a novel fixed-time sliding mode surface are developed to withstand the adverse influence of perturbations. Furthermore, an adaptive radial basis function neural network (RBFNN)-based sliding mode control algorithm is employed to approximate the continuous perturbations, so that the path-following LQ control problem can be further dealt with. The fixed-time stability and path-following results of the cart-pendulum robotic system are achieved by Lyapunov stability theory. A simulation example for a heavy material handling agricultural robot is proposed to verify the effectiveness of the developed method.

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Using neural network super‐twisting sliding mode to improve power control of a dual‐rotor wind turbine system in normal and unbalanced grid fault modes

Yahdou,

Djilali,

Bounadja

et al. 2024

Circuit Theory & Apps

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SummaryAccording to recent research work, increasing electric power generation is one of the significant advantages of the dual‐rotor wind turbine (DRWT) compared to the other types for the same wind speed. In this research work, a modified super‐twisting sliding mode control (STSMC) based on the neural network (NN) is suggested to regulate the stator powers of a DRWT‐based doubly‐fed induction generator (DFIG) in normal and unbalanced grid fault modes. The design of this strategy involves replacing the gains of conventional STSMC with the NN algorithm to enhance robustness, mitigate the impact of unbalanced grid voltage, and consequently improve the quality of the generated power of DRWT‐based DFIG. This forms the primary contribution of this work. The suggested strategy is compared with vector control (VC) and conventional STSMC in terms of reference tracking, power ripples, response dynamics, harmonic distortion of stator current, and the effect of an unbalanced grid fault. Finally, the utility and effectiveness of the designed controller are confirmed through computer simulations. Furthermore, when the grid is subjected to a 20% voltage drop, the results demonstrate that the suggested strategy reduced the total harmonic distortion (THD) value of the stator current by 12.92% compared to VC and by 9.29% compared to conventional STSMC.

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Neuro-adaptive singularity-free finite-time attitude tracking control of quadrotor UAVs

Cited by 6 publications

References 21 publications

Quadrotor attitude control by improved snake optimizer based adaptive switching disturbance rejection approach

Quadrotor attitude control by improved snake optimizer based adaptive switching disturbance rejection approach

Fixed‐time linear quadratic adaptive sliding mode control for a class of cart‐pendulum robots

Using neural network super‐twisting sliding mode to improve power control of a dual‐rotor wind turbine system in normal and unbalanced grid fault modes

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