Fuzzy adaptive sliding-mode control for MIMO nonlinear systems

By Shaocheng Tong, Han-Xiong Li. IEEE transactions on fuzzy systems, 2003

378 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/d3567e351e8c6c0c90f2caa6747bd35f123940bc

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. Shaocheng Tong
2. Yong-ming Li
3. Tie-shan Li
4. Gang Feng
5. Okyay Kaynak
6. Xinghuo Yu
7. Yan-Jun Liu
8. Wei Wang

In Control and Systems Engineering

1. Shaocheng Tong
2. Yong-ming Li
3. Tie-shan Li
4. Gang Feng
5. Xinghuo Yu
6. Peng Shi
7. Okyay Kaynak
8. Yanjun Liu

Citations in the corpus

• A Survey on Analysis and Design of Model-Based Fuzzy Control Systems (2006, methodology): “number of works on adaptive fuzzy control have been reported, see for example, [4], [18], [23], [41], [44], [70], [87], [97], [103], [150], [166], [171], [243], [256], [280], [291], [320], [321], [340], [341], and [346].”
• Sliding-Mode Control With Soft Computing: A Survey (2009, methodology): “In [77], the dynamics of (9) is used to enforce the reachability of the sliding modes for MIMO nonlinear systems represented in a similar form, as shown in above.”
• Hybrid Fuzzy Adaptive Output Feedback Control Design for Uncertain MIMO Nonlinear Systems With Time-Varying Delays and Input Saturation (2016, methodology): “The other is the feedback linearization technique that [1]–[5] used.”
• Robust Adaptive Tracking Control for Nonlinear Systems Based on Bounds of Fuzzy Approximation Parameters (2010, methodology): “has obtained much attention [16], [20], [27], [28], [33], [34].”