Lazy-Learning-Based Data-Driven Model-Free Adaptive Predictive Control for a Class of Discrete-Time Nonlinear Systems

2017 ◽  
Vol 28 (8) ◽  
pp. 1914-1928 ◽  
Author(s):  
Zhongsheng Hou ◽  
Shida Liu ◽  
Taotao Tian
Keyword(s):  
Nonlinear Systems ◽  
Predictive Control ◽  
Discrete Time ◽  
Data Driven ◽  
Lazy Learning ◽  
Model Free ◽  
Adaptive Predictive Control

Data-driven model-free sliding mode learning control for a class of discrete-time nonlinear systems

2020 ◽  
Vol 42 (13) ◽  
pp. 2533-2547
Author(s):  
Lei Cao ◽  
Shouli Gao ◽  
Dongya Zhao
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Sliding Mode ◽  
Learning Control ◽  
Linearization Method ◽  
Data Driven ◽  
Controlled System ◽  
Model Free ◽  
The Mathematical Model

This paper proposes a data-driven model-free sliding mode learning control (MFSMLC) for a class of discrete-time nonlinear systems. In this scheme, the control design does not depend on the mathematical model of the controlled system. The nonlinear system can be transformed into a dynamic linear data system by a novel dynamic linearization method. A recursive learning control algorithm is designed for the nonlinear system that can drive the sliding variable reach and remain on the sliding surface only by using output and input data. Moreover, the chattering is reduced because there is no non-smooth term in MFSMLC. After the strict stability analysis, the effectiveness of MFSMLC is validated by MATLAB simulations.

scholarly journals A New Data-Driven Model-Free Adaptive Control for Discrete-Time Nonlinear Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 126224-126233
Author(s):  
Kai Deng ◽  
Fanbiao Li ◽  
Chunhua Yang
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Data Driven ◽  
Model Free
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