A Novel Data-Driven Control Approach for a Class of Discrete-Time Nonlinear Systems

By Z. Hou, S. Jin. IEEE Transactions on Control Systems Technology, 2011

686 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/f0fb49cebb954213b767452757d75c748887fe74

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. Z. Hou
2. Huijun Gao
3. Shuangshuang Xiong
4. Zhuo Wang
5. Ronghu Chi
6. Wei He
7. Changyin Sun
8. Okyay Kaynak

Citations in the corpus

• Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems (2011, methodology): “Recently, model-free adaptive control (MFAC) approach has been proposed for a class of discrete-time SISO nonlinear systems with a systematic framework [24]–[30].”
• An Overview of Dynamic-Linearization-Based Data-Driven Control and Applications (2017, methodology): “With the continuous effort for more than 20 years, MFAC has been well developed with systematic works and analysis methods by the new concepts of the PPD and the PG, the new DLs of CFDL, PFDL, and FFDL, the systematic controller design methods, and the new definition and analysis method of robustnes”
• From model-based control to data-driven control: Survey, classification and perspective (2013, methodology): “So far, the effectiveness of the method has been verified in practical applications [28,34,37,39,61,64,87,88,131,140,153].”
• Data-Based Techniques Focused on Modern Industry: An Overview (2015, methodology): “Model-free adaptive control (MFAC) was proposed by Hou [18], in which a dynamic linearization data model with pseudopartial derivative (PPD) is employed to replace the general nonlinear discrete time system.”
• On Model-Free Adaptive Control and Its Stability Analysis (2019, methodology): “The other difficulties needed to be tackled are that the nonhomogeneous error dynamics inequality between e(k + 1) and e(k) is dominated by the mapping relationship of information vector HLy ,Lu (k) and HLy ,Lu (k − 1); however, those contraction mapping characteristic cannot be directly obtained by”
• Iterative Learning Control for a Flapping Wing Micro Aerial Vehicle Under Distributed Disturbances (2019, positive): “With simple structure and model-free nature [17], [18], iterative learning control (ILC) is widely used to suppress vibrations [19], track target trajectories [20], and reject time-varying disturbances [21]–[23].”