Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems

By Z. Hou, S. Jin. IEEE Transactions on Neural Networks, 2011

600 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/f693c9a254c841cd7eb0edf243e9f8d3af450660

How researchers see this paper

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

In Control and Systems Engineering

1. Huijun Gao
2. Shuangshuang Xiong
3. Z. Hou
4. Zhuo Wang
5. Ronghu Chi
6. Okyay Kaynak
7. Shen Yin
8. Xianwei Li

Citations in the corpus

• From model-based control to data-driven control: Survey, classification and perspective (2013, methodology): “(7) This dynamic linearization method can be easily extended to cases of MISO and MIMO nonlinear systems [52,54,65].”
• On Model-Free Adaptive Control and Its Stability Analysis (2019, methodology): “All the results of this study can be extended to MIMO nonlinear discrete-time systems [25].”
• An Overview of Dynamic-Linearization-Based Data-Driven Control and Applications (2017, methodology): “and MIMO nonlinear systems have also been done in [7] and [40].”
• Data-Based Techniques Focused on Modern Industry: An Overview (2015, background): “The system can be expressed by three representative dynamic linearization data models, with uniformly bounded PPD [17], [19].”