Adaptive Neural-Sliding Mode Control of a Quadrotor Vehicle with Uncertainties and Disturbances Compensation

Ullah, Mati; Zhao, Chunhui; Maqsood, Hamid; Nasir, Alam; Humayun, Muhammad; Hassan, M.; Alam, Faiz

doi:10.1109/icai55435.2022.9773561

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…In [26], the fuzzy logic sliding mode control strategy and the online adaptive estimation scheme were used to inhibit the influence of the actuator fault-tolerant control (FTC) without knowing advanced fault detection and diagnosis. Paper [27] introduced a finite-time extended disturbance observer-based adaptive neural sliding mode control approach, which not only eliminates chattering but also improves the network's learning speed. A selftuning sliding mode control strategy was proposed in [28], which proved that the tracking error is able to converge faster compared to the adaptive method.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Nonsingular Fast-Reaching Terminal Sliding Mode Control Based on Observer for Aerial Robots

Yang,

Xuan,

2024

Actuators

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In this article, an observer-based adaptive non-singular fast-reaching terminal sliding mode control strategy is proposed to tackle the problem of actuator faults and uncertain disturbance in aerial robot systems. Firstly, a model of an aerial robot system is established through dynamic analysis. Next, an adaptive observer, combined with a fast adaptive fault estimation (FAFE) algorithm, is proposed to estimate system states and actuator failure and compensate for faults in a precise and prompt manner. In addition, a non-singular fast terminal sliding surface is defined, taking into account the fast convergence of the tracking errors in order to provide appropriate trajectory tracking results. Since the upper bounds of the disturbances caused by the manipulator of the system in practice are unknown, the control approach may benefit from the addition of an adaptive control strategy that can suppress the influence of uncertain disturbances. The Lyapunov stability theory demonstrates that tracking errors are able to converge stably and quickly. In the end, the contrast experiment is conducted to exhibit the effectiveness of the proposed control strategy. The results demonstrate quicker convergence and improved estimating accuracy.

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Section: Introductionmentioning

confidence: 99%

Adaptive Nonsingular Fast-Reaching Terminal Sliding Mode Control Based on Observer for Aerial Robots

Yang,

Xuan,

2024

Actuators

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Adaptive Sliding Mode Control with an Extended Disturbance Observer for a Quadcopter Unmanned Aerial Vehicle: A Finite-Time Convergent Approach

Khan,

Gao,

et al. 2023

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

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Hybrid Backstepping Control of a Quadrotor Using a Radial Basis Function Neural Network

2023

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This article presents a hybrid backstepping consisting of two robust controllers utilizing the approximation property of a radial basis function neural network (RBFNN) for a quadrotor with time-varying uncertainties. The quadrotor dynamic system is decoupled into two subsystems: the position and the attitude subsystems. As part of the position subsystem, adaptive RBFNN backstepping control (ANNBC) is developed to eliminate the effects of uncertainties, trace the quadrotor’s position, and provide the desired roll and pitch angles commands for the attitude subsystem. Then, adaptive RBFNN backstepping is integrated with integral fast terminal sliding mode control (ANNBIFTSMC) to track the required Euler angles and improve robustness against external disturbances. The proposed technique is advantageous because the quadrotor states trace the reference states in a short period of time without requiring knowledge of dynamic uncertainties and external disturbances. In addition, because the controller gains are based on the desired trajectories, adaptive algorithms are used to update them online. The stability of a closed loop system is proved by Lyapunov theory. Numerical simulations show acceptable attitude and position tracking performances.

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Adaptive Neural-Sliding Mode Control of a Quadrotor Vehicle with Uncertainties and Disturbances Compensation

Cited by 3 publications

References 18 publications

Adaptive Nonsingular Fast-Reaching Terminal Sliding Mode Control Based on Observer for Aerial Robots

Adaptive Nonsingular Fast-Reaching Terminal Sliding Mode Control Based on Observer for Aerial Robots

Adaptive Sliding Mode Control with an Extended Disturbance Observer for a Quadcopter Unmanned Aerial Vehicle: A Finite-Time Convergent Approach

Hybrid Backstepping Control of a Quadrotor Using a Radial Basis Function Neural Network

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