Adaptive Backstepping Terminal Sliding Mode Control of Nonlinear System Using Fuzzy Neural Structure

Gong, Xiaoyu; Fu, Wen; Bian, Xingao; Fei, Juntao

doi:10.3390/math11051094

Cited by 7 publications

(6 citation statements)

References 43 publications

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“…The ultimate goal of orthogonal modeling is to obtain a set of optimal θ values so that the least squares cost function J of the model is minimized [21], where…”

Section: Dynamic Model Configuration Optimization Based On Multivaria...mentioning

confidence: 99%

Time-Domain Identification Method Based on Data-Driven Intelligent Correction of Aerodynamic Parameters of Fixed-Wing UAV

Yang,

Zang,

Liu

et al. 2023

Drones

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In order to overcome the influence of complex environmental disturbance factors such as nonlinear time-varying characteristics on the dynamic control performance of small fixed-wing UAVs, the nonlinear expression relationship of neural networks (NNs) is combined with the recursive least squares (RLSs) identification algorithm. This paper proposes a hybrid aerodynamic parameter identification method based on NN-RLS offline network training and online learning correction. The simulation results show that compared with the real value of the identification value obtained by this algorithm, the residual error of the moment coefficient is reduced by 69%, and the residual error of the force coefficient is reduced by 89%. Under the same identification accuracy, the identification time is shortened from the original 0.1 s to 0.01 s. Compared with traditional identification algorithms, better estimation results can be obtained. By using this algorithm to continuously update the NN model and iterate repeatedly, iterative learning for complex dynamic models can be realized, providing support for the optimization of UAV control schemes.

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“…The ultimate goal of orthogonal modeling is to obtain a set of optimal θ values so that the least squares cost function J of the model is minimized [21], where…”

Section: Dynamic Model Configuration Optimization Based On Multivaria...mentioning

confidence: 99%

Time-Domain Identification Method Based on Data-Driven Intelligent Correction of Aerodynamic Parameters of Fixed-Wing UAV

Yang,

Zang,

Liu

et al. 2023

Drones

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“…In view of the above problems, scholars have done a lot of research. Reference 25 used a neural network strategy to obtain synovial gain. Although this scheme can eliminate chattering, the design of variable parameters is more complex.…”

Section: Introductionmentioning

confidence: 99%

Research on speed sensorless control strategy of permanent magnet synchronous motor based on fuzzy super-twisting sliding mode observer

Song,

Liu,

Ren

et al. 2024

Science Progress

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Aiming at the problems of poor adjustment effect, weak anti-disturbance ability, and low robustness of the traditional sliding mode algorithm for permanent magnet synchronous motor speed sensorless, a permanent magnet synchronous motor speed observation method combining super-twisting sliding mode control algorithm and fuzzy control is proposed to accelerate the convergence speed of the system and improve the anti-disturbance ability. Fuzzy rules are used to solve the problem of obtaining the upper bound of the boundary function in the super-twisting algorithm. Moreover, the fuzzy algorithm is used to output the variable sliding mode gain instead of the fixed sliding mode coefficient to improve the system robustness and suppress the jitter. The simulation results show that the overshoot of the control system is 4%, the lag time is not more than 0.003 ms, the speed error is not more than 1%, and the response and adjustment time is not more than 0.02 s. The proposed control strategy improves the tracking accuracy and response speed of the system, suppresses the sliding mode chattering, and enhances the anti-interference ability of the system.

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“…Nonetheless, in engineering applications, the upper bounds of the disturbances and parametric uncertainties are not always available. Several adaptive control techniques such as adaptive robust NFTSMC [17], adaptive backstepping [18], adaptive backstepping TSMC [19] have been proposed to estimate and mitigate the disturbances thereby enhancing the following of the target attitude and position of the quadrotors. In [14], an adaptive PID controller was proposed to realize the tracking of orientation and translation of a quadrotor.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Backstepping and Sliding Mode Control of a Quadrotor

maaruf,

Gulzar,

Abubakar

2024

Preprint

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Quadrotors are increasingly employed for both civilian and military applications. Recently, researchers have combined different control and estimation schemes to come up with a hybrid control structure to improve the robustness and tracking performance of the quadrotors. To further enhance the tracking precision of quadrotors subjected to parametric variations and environmental disturbances, this article proposes a new robust adaptive hybrid control architecture. In this study, the quadrotor model is divided into altitude, attitude, and position subsystems for which appropriate control methods are designed. A fractional-order sliding mode control with adaptive gain (AFSMC) is designed to enhance the tracking of the altitude subsystem. A robust backstepping control with adaptive gain (RAB) is developed for the horizontal position to generate the required roll and pitch orientations. A nonsingular fast terminal sliding mode control (NFTSMC) is incorporated with a finite-time disturbance observer (FDO) to accurately suppress the disturbances, follow the target rotation angles, and attain finite-time stability. The compounded control structure ensures accurate, fast, and robust tracking. The efficacy of the developed hybrid control scheme is assessed via simulations and comparisons with existing control methods.

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Adaptive Backstepping Terminal Sliding Mode Control of Nonlinear System Using Fuzzy Neural Structure

Cited by 7 publications

References 43 publications

Time-Domain Identification Method Based on Data-Driven Intelligent Correction of Aerodynamic Parameters of Fixed-Wing UAV

Time-Domain Identification Method Based on Data-Driven Intelligent Correction of Aerodynamic Parameters of Fixed-Wing UAV

Research on speed sensorless control strategy of permanent magnet synchronous motor based on fuzzy super-twisting sliding mode observer

Adaptive Backstepping and Sliding Mode Control of a Quadrotor

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