Fractional-Order Linear Active Disturbance Rejection Control Design and Optimization Based Improved Sparrow Search Algorithm for Quadrotor UAV with System Uncertainties and External Disturbance

Hu, Yunlong; Su, Jiangcheng; Zhao, Mingfei; Ai, Shaojie

doi:10.3390/drones6090229

Cited by 15 publications

(2 citation statements)

References 30 publications

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“…Many existing observers have been previously reported in the literature [14,15,21] for the FJR system. Furthermore, the extended state observer (ESO) has been proven as being a promising observer tool in the active disturbance rejection control techniques for estimating states and disturbance, which have been applied for different systems such as drones [23,24]. However, the estimation error of the states and disturbances in the above observer works can only approach to zero asymptotically and slowly, and they are sensitive to the initial conditions.…”

Section: Introductionmentioning

confidence: 99%

Practically Robust Fixed-Time Convergent Sliding Mode Control for Underactuated Aerial Flexible JointRobots Manipulators

Rsetam

Cao

Wang

et al. 2022

Drones

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The control of an aerial flexible joint robot (FJR) manipulator system with underactuation is a difficult task due to unavoidable factors, including, coupling, underactuation, nonlinearities, unmodeled uncertainties, and unpredictable external disturbances. To mitigate those issues, a new robust fixed-time sliding mode control (FxTSMC) is proposed by using a fixed-time sliding mode observer (FxTSMO) for the trajectory tracking problem of the FJR attached to the drones system. First, the underactuated FJR is comprehensively modeled and converted to a canonical model by employing two state transformations for ease of the control design. Then, based on the availability of the measured states, a cascaded FxTSMO (CFxTSMO) is constructed to estimate the unmeasurable variables and lumped disturbances simultaneously in fixed-time, and to effectively reduce the estimation noise. Finally, the FxTSMC scheme for a high-order underactuated FJR system is designed to guarantee that the system tracking error approaches to zero within a fixed-time that is independent of the initial conditions. The fixed-time stability of the closed-loop system of the FJR dynamics is mathematically proven by the Lyapunov theorem. Simulation investigations and hardware tests are performed to demonstrate the efficiency of the proposed controller scheme. Furthermore, the control technique developed in this research could be implemented to the various underactuated mechanical systems (UMSs), like drones, in a promising way.

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Section: Introductionmentioning

confidence: 99%

Practically Robust Fixed-Time Convergent Sliding Mode Control for Underactuated Aerial Flexible JointRobots Manipulators

Rsetam

Cao

Wang

et al. 2022

Drones

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show abstract

“…Under the strong external disturbance, the UAV cannot maintain the desired attitude, which often leads to the failure of the mission. This requires its control system to have strong robustness and anti-interference ability [13].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Neural Network Dynamic Inverse Control Strategy for Quadrotor UAV Based on Atmospheric Turbulence

Yang

Cheng

et al. 2022

Applied Sciences

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Quadrotor UAV is vulnerable to external interference, which affects search and rescue. In this paper, a fuzzy neural network dynamic inverse controller (FNN-DIC) is designed to eliminate the instability of the attitude angle caused by atmospheric turbulence. Considering the complexity of atmospheric turbulence, the component model of atmospheric turbulence is obtained firstly based on the Dryden model, using Gaussian white noise as a random input signal and a designed shaping filter. Combined with the Newton-Euler equation, a nonlinear dynamic model for the quadrotor UAV with atmospheric disturbance is established. While the traditional nonlinear dynamic inverse cancels the nonlinearity of the controlled object, it relies on precise mathematical models. The fuzzy neural network can adaptively compensate for the inaccurate part of the model and the inverse error of the model caused by the external disturbance, and the stability of the control system is strictly proved by using the Lyapunov function. The experiments are carried out on the simulation platform, and the results show that the FNN method can ensure that the quadrotor UAV can still fly smoothly against strong disturbances, and that robustness of the system is significantly improved.

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Active disturbance rejection control for spacecraft relative motion in libration point orbits subject to actuator saturation and time-delays

Li,

Chen,

et al. 2024

Advances in Space Research

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Fractional-Order Linear Active Disturbance Rejection Control Design and Optimization Based Improved Sparrow Search Algorithm for Quadrotor UAV with System Uncertainties and External Disturbance

Cited by 15 publications

References 30 publications

Practically Robust Fixed-Time Convergent Sliding Mode Control for Underactuated Aerial Flexible JointRobots Manipulators

Practically Robust Fixed-Time Convergent Sliding Mode Control for Underactuated Aerial Flexible JointRobots Manipulators

Fuzzy Neural Network Dynamic Inverse Control Strategy for Quadrotor UAV Based on Atmospheric Turbulence

Active disturbance rejection control for spacecraft relative motion in libration point orbits subject to actuator saturation and time-delays

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