Control Design for Interval Type-2 Fuzzy Systems Under Imperfect Premise Matching

By Hak-Keung Lam, Hongyi Li, Christian Deters, Emanuele Lindo Secco, Helge A. Wurdemann, Kaspar Althoefer. IEEE transactions on industrial electronics (1982. Print), 2014

350 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/753911b4a959b033f2caee83e8afeed775f49aba

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. Hongyi Li
2. Qi Zhou
3. Peng Shi
4. Haiping Du
5. Hak-Keung Lam
6. Yanming Wu
7. Yingnan Pan
8. Yabin Gao

In Control and Systems Engineering

1. Hongyi Li
2. Qi Zhou
3. Haiping Du
4. Hak-Keung Lam
5. Peng Shi
6. Yingnan Pan
7. Yanming Wu
8. Yabin Gao

Citations in the corpus

• Fuzzy Control Systems: Past, Present and Future (2019, background): “However, for stability analysis and control design, the lower and upper MFs have to be simultaneously considered leading to more elaborated manipulations and computational burden [92], [93].”
• Control of Nonlinear Networked Systems With Packet Dropouts: Interval Type-2 Fuzzy Model-Based Approach (2015, neutral): “Referring to the proof in [37], at any time, the equality ∑ς+1 l=1 ρijl(σ (k)) = 1 is ensured by only one ρijl(σ (k)) = 1 for each fixed i, j value.”
• Observer-Based Fault Detection for Nonlinear Systems With Sensor Fault and Limited Communication Capacity (2016, methodology): “Practical examples, such as the inverted pendulum system and the model of bolt-tightening tool mounted on a robot arm [16], have shown the superiority of IT2 fuzzy model.”
• Adaptive Sliding Mode Control for Interval Type-2 Fuzzy Systems (2016, background): “Remark 1: As stated in [20], the parametric uncertainties hidden in the membership function of each fuzzy rule are represented by the LUMFs.”
• 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 ”