Novel Data and Neural Network-Based Nonlinear Adaptive Switching Control Method

Zhang, Yajun; Niu, Hong; Tao, Jinmei; Li, Xusheng

doi:10.1109/tnnls.2020.3029113

Cited by 5 publications

(2 citation statements)

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“…Remark 4. It is noted that FLS and NN methods have a good approximation performance to continuous functions, but poor approximation ability to discontinuous functions [27,29]. However, in practical applications for the continuum robot, the abrupt and intermittent actuator deadzones/faults may be discontinuous.…”

Section: Design Of Anftsmcmentioning

confidence: 99%

“…A NN-based adaptive attitude controller was designed for the spacecraft [28]. Moreover, an adaptive switching control method using NN was proposed for a nonlinear system [29]. However, it is worth noting that FLS and NN methods mainly have good approximation ability to continuous functions, but poor approximation capability to discontinuous functions.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Approximation Sliding-Mode Control of an Uncertain Continuum Robot with Input Nonlinearities and Disturbances

2024

Applied Bionics and Biomechanics

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This paper develops an adaptive nonsingular fast terminal sliding-mode control (ANFTSMC) scheme for the continuum robot subjected to uncertain dynamics, external disturbances, and input nonlinearities (e.g., actuator deadzones/faults). Concretely, a function approximation technique (FAT) is utilized to estimate unknown robot dynamics and actuator deadzones/faults online. Furthermore, a disturbance observer (DO) is devised to make up for unknown external disturbances. Then, an ANFTSMC scheme combined with FAT and DO is developed, to expedite the restoration of the stability for the continuum robot. The proposed ANFTSMC not only can retain the benefits of traditional terminal sliding-mode control (TSMC), containing easy enforcement, quick response, and robustness to uncertainties but also dispose of the latent singularity for traditional faster TSMC designs. Afterward, the simulation results show that the proposed controller can effectively improve the trajectory tracking accuracy of the continuum robot, and the tracking root-mean-square errors are 0.0115 and 0.0128 rad. Finally, the effectiveness of ANFTSMC scheme is validated by experiments.

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Section: Design Of Anftsmcmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%