Stability Analysis of Interval Type-2 Fuzzy-Model-Based Control Systems

By Hak-Keung Lam, Lakmal D. Seneviratne. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), 2008

452 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/403378af6ad1d958d35fa74a73e14b6c742fe52d

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. Hak-Keung Lam
2. Hongyi Li
3. Peng Shi
4. Yanming Wu
5. Yingnan Pan
6. Yabin Gao
7. Kaspar Althoefer
8. Luka Eciolaza

In Control and Systems Engineering

1. Hongyi Li
2. Hak-Keung Lam
3. Peng Shi
4. Yingnan Pan
5. Yanming Wu
6. Yabin Gao
7. Kaspar Althoefer
8. Luka Eciolaza

Citations in the corpus

• Fuzzy Control Systems: Past, Present and Future (2019, background): “Hence, type-2 T-S fuzzy systems are very useful in the cases where exact MFs are difficult to be chosen and/or there is a need to cope with large amounts of uncertainties [89], [90].”
• Security-Based Fuzzy Control for Nonlinear Networked Control Systems With DoS Attacks via a Resilient Event-Triggered Scheme (2022, methodology): “In addition, considering the uncertain parameters in the system, an interval type-2 (IT2) fuzzy modeling and control method under the fuzzy-model-based framework was proposed for the first time in [21] and [22] that the imperfect premise matching concept and membership-function-dependent techniques ”
• Control of Nonlinear Networked Systems With Packet Dropouts: Interval Type-2 Fuzzy Model-Based Approach (2015, unknown): “In order to obtain a more general IT2 T-S FM, Lam and Seneviratne [35] extended it.”
• Observer-Based Fault Detection for Nonlinear Systems With Sensor Fault and Limited Communication Capacity (2016, methodology): “More recently, based on type-2 fuzzy set [12], an interval type-2 (IT2) fuzzy-model-based system was proposed to handle the parameter uncertainties of the nonlinear plant in [13]–[15].”
• Control Design for Interval Type-2 Fuzzy Systems Under Imperfect Premise Matching (2014, methodology): “Recently, some research has been done on system control and stability analysis based on the existing framework of type-2 fuzzy systems [39], [44]–[48].”