This paper investigates the trajectory-tracking control problem for manipulators subject to stochastic payload variations and composite disturbances. The manipulator dynamics are modeled as a Markov jump system to capture random mode switching. To ensure high-precision tracking, a novel reinforcement learning (RL)-base...
Dan Li, Hua-Guang Zhang, Yang Cui et al.· IEEE Transactions on Automat...· 0 citations
This paper addresses the trajectory tracking control problem of nonlinear systems subject to uncertain disturbances by proposing a unified prescribed-time control framework integrating disturbance observation and performance constraints. First, a prescribed-time disturbance observer with smooth adaptive gains and a tim...
Zai-Hong Zheng, Dan Li, Huan-Qing Wang et al.· ISA transactions· 0 citations
The proposed FTSMC achieves the lowest Integral Squared Error, Integral Absolute Error, and Root Mean Square Error among the compared methods, reducing the ISE by up to a factor of 287, the IAE by up to a factor of 11, and the RMSE by up to a factor of 17.
Saim Ahmed, Z. Haider, A. T. Azar· An International Journal of...· 0 citations
This paper investigates trajectory-tracking control for a wheeled mobile robot under model uncertainty and bounded velocity disturbances. To improve tracking accuracy, robustness and chattering suppression, a kinematic model is established and a sliding-mode variablestructure controller with a saturation-type reaching...
Fang Liu, Chun-Gang Wang, Gang Du· 2026 3rd International Confe...· 0 citations
This paper proposes an adaptive fractional-order nonsingular terminal sliding mode control framework for trajectory tracking of robotic manipulators under unknown disturbances and model uncertainties. First, a fractional-order dynamic model is derived to more accurately capture the complex electromechanical behavior...
M. Tabatabaei, Hadi Delavari· Journal of Intelligent &...· 0 citations