Design of RBFNN-based adaptive sliding mode control strategy for active rehabilitation robot

P Zhang, J Zhang, Z Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
… the control system [27]–[29] and to deal with periodic disturbances [31]. Therefore, in this
article, a RBFNN-based adaptive sliding mode control … of trajectory tracking for lower limb robot

Adaptive sliding mode attitude control of two-wheel mobile robot with an integrated learning-based RBFNN approach

H Pang, M Liu, C Hu, F Zhang - Neural Computing and Applications, 2022 - Springer
adaptive sliding mode controller is … the trajectory tracking control of TWMR considering its
dynamics and kinematics characteristics together. Specifically, the trajectory tracking controller

RBFNN-Based Adaptive Integral Sliding Mode Feedback and Feedforward Control for a Lower Limb Exoskeleton Robot

T Yuan, C Zhang, F Yi, P Lv, M Zhang, S Li - Electronics, 2024 - mdpi.com
… In this section, we propose an adaptive trajectory tracking method that integrates a PID,
feedforward, and RBF neural network-based sliding mode control method to reduce the tracking

Fault-tolerant attitude tracking control for carrier-based aircraft using RBFNN-based adaptive second-order sliding mode control

H Xiao, Z Zhen, Y Xue - Aerospace Science and Technology, 2023 - Elsevier
… integral (PI) sliding mode variable are designed respectively … RBFNN-based adaptive
second-order sliding mode control (… improves attitude tracking performance. Furthermore, the …

A novel trajectory tracking control approach for uncertain 6-DOF manipulators based on fuzzy sliding mode of radial basis function neural network

Y Liu, B Chen, L Ma, S Yang, R Li… - … of Systems and Control …, 2023 - journals.sagepub.com
… external disturbance and model error, the trajectory tracking of … , a sliding mode control
method combined fuzzy controller and … of robotic manipulator for handling an unknown payload. …

Trajectory tracking based on neural network sliding mode controller

JY Yu - Authorea Preprints, 2023 - authorea.com
robotic systems have mostly been based on state feedback control schemes such as sliding
mode control … The RBFNN-based control scheme is often used to identify the uncertain items …

Adaptive sliding mode control design for nonlinear unmanned surface vessel using RBFNN and disturbance-observer

Z Chen, Y Zhang, Y Nie, J Tang, S Zhu - Ieee Access, 2020 - ieeexplore.ieee.org
… To make the trajectory tracking superiority of our control … Zhu, ‘‘RBFNN-based adaptive
sliding mode control design for … control of robotic and mechatronic systems, such as nonlinear …

Neural network-based tracking control of uncertain robotic systems: predefined-time nonsingular terminal sliding-mode approach

Y Sun, Y Gao, Y Zhao, Z Liu, J Wang… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
… been devoted to the study of nonsingular terminal slidingmode control (NTSMC) [9]. To … 1)
A novel RBFNN-based predefined-time NTSMC strategy is developed for trajectory tracking of …

RBFNN based terminal sliding mode adaptive control for electric ground vehicles after tire blowout on expressway

L Yang, M Yue, Y Liu, L Guo - Applied Soft Computing, 2020 - Elsevier
… based terminal sliding mode controlcontrol scheme and methods, and the comprehensive
performance of TSMC+RBFNN and TSMC schemes in maintaining original trajectory tracking

Adaptive neural network fixed-time sliding mode control for trajectory tracking of underwater vehicle

Z Zhu, Z Duan, H Qin, Y Xue - Ocean Engineering, 2023 - Elsevier
… disturbances, designing effective trajectory tracking controllers and disturbance observers
… of tracking errors, a trajectory-tracking controller based on fixed-time sliding mode control (…