Fuzzy Neural Network-Based Adaptive Control for a Class of Uncertain Nonlinear Stochastic Systems

By Chun Lung Philip Chen, Yanjun Liu, Guoxing Wen. IEEE Transactions on Cybernetics, 2014

478 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/4509d415e5801aa2c33544168aac572bc13406dd

How researchers see this paper

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

In Artificial Intelligence

1. Wei He
2. Changyin Sun
3. Chun Lung Philip Chen
4. Yanjun Liu
5. Hongyi Li
6. Huijun Gao
7. Haiping Du
8. Qi Zhou

In Computational Theory and Mathematics

1. Wei He
2. Changyin Sun
3. Yanjun Liu
4. Yiting Dong
5. Zhao Yin
6. Chun Lung Philip Chen
7. David Ofosu Amoateng
8. Hongyi Li

In Control and Systems Engineering

1. Wei He
2. Hongyi Li
3. Changyin Sun
4. Yanjun Liu
5. Yiting Dong
6. Chun Lung Philip Chen
7. Shaocheng Tong
8. Zhao Yin

Citations in the corpus

• Neural Network Control of a Robotic Manipulator With Input Deadzone and Output Constraint (2016, methodology): “In [12], adaptive fuzzy neural networks are used to approximate a nonlinear stochastic sys-tem with unknown functions.”
• Adaptive Neural Network Control of a Robotic Manipulator With Time-Varying Output Constraints (2017, background): “In [33], fuzzy NN-based adaptive control is designed for a class of uncertain nonlinear stochastic systems.”
• Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems (2016, methodology): “By applying approximator-based adaptive backstepping technique, the tracking or regulation control problem of the nonlinear strict-feedback or semi-strict-feedback systems can be well dealt with [19]–[23].”
• Prescribed Performance Control of Uncertain Euler–Lagrange Systems Subject to Full-State Constraints (2018, unknown): “linear systems with nonparametric uncertainties [3], [6], [14], [15], [31].”
• Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation (2016, background): “In [24], an adaptive control for a class of nonlinear stochastic systems with unknown functions is studied.”
• Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints (2016, unknown): “Using Young’s inequality [50], we obtain”
• Adaptive Sliding Mode Control for Interval Type-2 Fuzzy Systems (2016, background): “[9] proposed a novel fuzzy adaptive control for nonlinear stochastic systems.”
• 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, methodology): “Furthermore, it has been veri-fied that the NN method is good at dealing with nonlinear systems and has excellent approximation effects [33], [34].”