Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning

By Wei He, Yiting Dong. IEEE Transactions on Neural Networks and Learning Systems, 2018

591 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/9e3a90c2a638d9bbea596ebdd08704f4eb3212e6

How researchers see this paper

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

In Computational Theory and Mathematics

1. Wei He
2. Changyin Sun
3. Tong Wang
4. Kangkang Sun
5. Jianbin Qiu
6. Huijun Gao
7. Shaoshuai Mou
8. Yiting Dong

In Control and Systems Engineering

1. Jianbin Qiu
2. Wei He
3. Changyin Sun
4. Yunan Chen
5. Zichen Yan
6. Huijun Gao
7. Tong Wang
8. Kangkang Sun

Citations in the corpus

• Adaptive Fuzzy Control for Nontriangular Structural Stochastic Switched Nonlinear Systems With Full State Constraints (2019, background): “Remark 3: Based on the adaptive control techniques in [28]– [36] and [39]–[41], the results for the case of pure-feedback nonlinear systems can be easily obtained by combining the approach proposed in [35].”
• Adaptive Neural Network Control of a Flapping Wing Micro Aerial Vehicle With Disturbance Observer (2017, background): “In 2015, He et al. [35], [36] and Sun et al. [37] employed the NN control with full state and output feedback to work out tracking control issues of an n-link robot for rehabilitation training with uncertainties.”