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

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 Compact Model-Free Adaptive Control Algorithm for Discrete-Time Nonlinear Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 141062-141071 ◽  
Author(s):  
Xiaofei Zhang ◽  
Hongbin Ma ◽  
Xinghong Zhang ◽  
You Li
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Control Algorithm ◽  
Compact Model ◽  
Model Free ◽  
Adaptive Control Algorithm

A Novel Higher-Order Model-Free Adaptive Control for a Class of Discrete-Time SISO Nonlinear Systems

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Shangtai Jin ◽  
Zhongsheng Hou ◽  
Ronghu Chi
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Higher Order ◽  
Control Input ◽  
Order Model ◽  
Control Approach ◽  
Model Free ◽  
Input And Output ◽  
Control Scheme

In this work, a novel higher-order model-free adaptive control scheme is presented based on a dynamic linearization approach for a class of discrete-time single input and single output (SISO) nonlinear systems. The control scheme consists of an adaptive control law, a parameter estimation law, and a reset mechanism. The design and analysis of the proposed control approach depends merely on the measured input and output data of the controlled plant. The control performance is improved by using more information of control input and output error measured from previous sampling time instants. Rigorous mathematical analysis is developed to show the bounded input and bounded output (BIBO) stability of the closed-loop system. Two simulation comparisons show the effectiveness of the proposed control scheme.

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