A Combined Backstepping and Small-Gain Approach to Robust Adaptive Fuzzy Output Feedback Control

By Shaocheng Tong, Xianglei He, Huaguang Zhang. IEEE transactions on fuzzy systems, 2009

405 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/4588f23f322dd4c350b8094cf43a076a356f1e1d

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. Mou Chen
2. Xiaoping Liu
3. Chong Lin
4. Bing Chen
5. Gang Tao
6. Bin Jiang
7. Shuzhi Sam Ge
8. Wei He

In Control and Systems Engineering

1. Shaocheng Tong
2. Mou Chen
3. Yong-ming Li
4. Xiaoping Liu
5. Bing Chen
6. Shuzhi Sam Ge
7. Chong Lin
8. Gang Tao

Citations in the corpus

• Adaptive Fuzzy Control of a Class of Nonlinear Systems by Fuzzy Approximation Approach (2012, background): “The first one estimates each element of Wi [36], [37], and the second one estimates its norm [45].”
• Adaptive Neural Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis (2014, background): “Recently, approximation-based adaptive neural (or fuzzy) control schemes have been found to be particularly useful for the control of highly uncertain, nonlinear and complex systems, and many interesting research results have been obtained in [18]–[30] for deterministic nonlinear systems and in [31]”
• Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation (2015, methodology): “A combined backstepping and small-gain approach was developed for the robust adaptive fuzzy output feedback control design in [22].”