Adaptive Fuzzy Output Feedback Dynamic Surface Control of Interconnected Nonlinear Pure-Feedback Systems

By Yong-ming Li, Shaocheng Tong, Tie-shan Li. IEEE Transactions on Cybernetics, 2015

389 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/f065c17b9e5252091afffe9ca7b562f129886e16

How researchers see this paper

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

In Aerospace Engineering

1. Mou Chen
2. Chun-Yi Su
3. Qi Zhou
4. Haiping Du
5. Lijie Wang
6. Chenguang Yang
7. Chengwei Wu
8. Hongyi Li

In Computer Networks and Communications

1. Hongyi Li
2. Haiping Du
3. Chenguang Yang
4. Qi Zhou
5. Gang Tao
6. Hak-Keung Lam
7. Jiahui Wang
8. Lijie Wang

In Control and Systems Engineering

1. Hongyi Li
2. Mou Chen
3. Qi Zhou
4. Haiping Du
5. Gang Tao
6. Shaocheng Tong
7. Chenguang Yang
8. Lijie Wang

Citations in the corpus

• Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone (2016, background): “MANY physical systems such as power system, aerospace system, chemical engineering system, and telecommunication network are composed of interconnections of lower-dimensional subsystems [1]–[4].”
• Event-Triggered Fault Detection of Nonlinear Networked Systems (2017, background): “The authors in [12] designed a novel adaptive fuzzy output feedback controller for purefeedback interconnected nonlinear systems with unmeasured states.”
• Adaptive Fuzzy Control for Nonstrict-Feedback Systems With Input Saturation and Output Constraint (2017, background): “2557222 control, which has the ability to adjust the adaptive parameters of the controller by online learning [29]–[32].”
• Teleoperation Control Based on Combination of Wave Variable and Neural Networks (2017, methodology): “In [21]–[23], adaptive fuzzy control was used for identification of the unknown nonlinear control system.”
• Adaptive Sliding Mode Control for Interval Type-2 Fuzzy Systems (2016, methodology): “In order to compensate the uncertainties or faults, several control methods have been applied, such as fuzzy control [26], [27], adaptive control [28]–[30], sliding mode control (SMC) [31]–[33], and backstepping control [4], [34].”