Dec 7, 2021 · Considering the complexity of dynamic and friction modeling, this paper aims to develop an adaptive trajectory tracking control scheme for robot ...
Abstract. Purpose – Considering the complexity of dynamic and friction modeling, this paper aims to develop an adaptive trajectory tracking control scheme.
Jan 3, 2022 · This paper aims to develop an adaptive trajectory tracking control scheme for robot manipulators in a universal unmodeled method, avoiding complicated modeling ...
Recently, for more complicated systems, researchers have started to represent Lyapunov functions (but not their associated controllers) using neural networks.
Moreover, the control algorithm is designed based on Barrier Lyapunov Function (BLF) to constrain output error. Findings Lyapunov stability analysis ...
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Abstract:This paper focuses on a novel adaptive sliding mode control (NASMC) of robot manipulator based on RBF (radial basis function) neural network and ...
Barrier Lyapunov function-based robot control with an augmented neural network approximator. Z Zhang, Q Wu, X Li, C Liang. Industrial Robot: the international ...
Oct 22, 2024 · The Neural Lyapunov Control (NLC) method is one such example. This approch combines Artificial Neural Networks with Satisfiability Modulo ...
Mar 12, 2024 · We demonstrate that our fine-tuning method can significantly boost the performance of the verification-aided learning framework on examples of ...
Abstract—In this paper, we present a backstepping adap- tive hybrid force/position control based on Barrier Lyapunov. Function for a robotic manipulator to ...
Missing: approximator. | Show results with:approximator.