scholarly journals Design of a Data-Driven Adaptive Control based on OFSP for Discrete Nonlinear Systems

2018 ◽  
Vol 2018 (0) ◽  
pp. 86-91
Author(s):  
Zhe Guan ◽  
Shin Wakitani ◽  
Ikuro Mizumoto ◽  
Toru Yamamoto
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Data Driven ◽  
Discrete Nonlinear Systems

Adaptive Control Approaches for Nonlinear Systems: Retrospect and Prospects

2015 ◽  
Vol 719-720 ◽  
pp. 336-345
Author(s):  
Hong Liang Rao
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Data Driven ◽  
Research Progress ◽  
New Classification ◽  
Future Directions ◽  
Main Research ◽  
Model Driven ◽  
Classification Framework ◽  
State Of Art

This paper discusses the state-of-art of adaptive control approaches for nonlinear systems to date and presents a new classification framework, in which the existing adaptive control approaches can be broadly classified into two categories: model-driven methods and data-driven methods. The principle, main research progress, and inherent problems of these methods are reviewed. Finally, some practical considerations and future directions are also briefly explored and discussed.

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

Adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics

2021 ◽  
pp. 014233122098563
Author(s):  
Fei Shen ◽  
Xinjun Wang ◽  
Xinghui Yin
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Dead Zone ◽  
Small Neighborhood ◽  
Unmodeled Dynamics ◽  
Stochastic Nonlinear Systems ◽  
Dynamic Surface ◽  
Barrier Lyapunov Function ◽  
Full State

This paper investigates the problem of adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics. To stabilize such a system, a dynamic signal is introduced to dominate unmodeled dynamics and an assistant signal is constructed to compensate for the effect of the dead zone. Dynamic surface control is used to solve the “complexity explosion” problem in traditional backstepping design. Two cases of symmetric and asymmetric Barrier Lyapunov functions are discussed respectively in this paper. The proposed Barrier Lyapunov function based on backstepping method can ensure that the output tracking error converges in the small neighborhood of the origin. This control scheme can ensure that semi-globally uniformly ultimately boundedness of all signals in the closed-loop system. Two simulation cases are proposed to verify the effectiveness of the theoretical method.

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