Adaptive Prescribed Performance Motion Control of Servo Mechanisms with Friction Compensation

By Jing Na, Qiang Chen, Xuemei Ren, Yu Guo. IEEE transactions on industrial electronics (1982. Print), 2014

485 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/fd00b6debb95a4045121c73cb3bf475afb2a56f6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Mou Chen
2. Jun Yang
3. Yanjun Liu
4. Shihua Li
5. Chun Lung Philip Chen
6. Lei Guo
7. Rongxin Cui
8. Wen‐Hua Chen

In Mechanical Engineering

1. Jun Yang
2. Shihua Li
3. Lei Guo
4. Wen‐Hua Chen
5. Yunda Yan
6. Mou Chen

Citations in the corpus

• Adaptive Neural Network Control of AUVs With Control Input Nonlinearities Using Reinforcement Learning (2017, background): “tainties should be considered in designing an appropriate controller [16]–[23].”
• Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay (2019, background): “The main control schemes for preventing the violation of constraints include reference governors in [26], model predictive control in [27], extremum seeking control in [28], and prescribed performance control in [29]–[32].”
• Manipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks (2017, background): “Particularly, using neural networks for the control of robot manipulators have attracted much attention and various related schemes and methods have been proposed and investigated [3], [5], [8], [24], [25].”
• Disturbance/Uncertainty Estimation and Attenuation Techniques in PMSM Drives—A Survey (2017, methodology): “Adaptive Control Strong adaptiveness against severe parameter uncertainty, Sensitive to structural uncertainties such as [14]–[18]”