Adaptive fuzzy modelling and control for discrete-time nonlinear uncertain systems

2005 ◽  
Author(s):  
Ruiyun Qi ◽  
M.A. Brdys
Keyword(s):  
Discrete Time ◽  
Uncertain Systems ◽  
Fuzzy Modelling ◽  
Adaptive Fuzzy ◽  
Nonlinear Uncertain Systems ◽  
And Control

scholarly journals Composite adaptive NN learning and control for discrete-time nonlinear uncertain systems in normal form

2020 ◽  
Vol 390 ◽  
pp. 168-184
Author(s):  
Jingting Zhang ◽  
Chengzhi Yuan ◽  
Cong Wang ◽  
Paolo Stegagno ◽  
Wei Zeng
Keyword(s):  
Normal Form ◽  
Discrete Time ◽  
Uncertain Systems ◽  
Nonlinear Uncertain Systems ◽  
And Control

Small Fault Detection of Discrete-Time Nonlinear Uncertain Systems

2019 ◽  
pp. 1-15 ◽  
Author(s):  
Jingting Zhang ◽  
Chengzhi Yuan ◽  
Paolo Stegagno ◽  
Haibo He ◽  
Cong Wang
Keyword(s):  
Fault Detection ◽  
Discrete Time ◽  
Uncertain Systems ◽  
Small Fault ◽  
Nonlinear Uncertain Systems

Adaptive Dynamics Learning for Small Fault Detection of Discrete-Time Nonlinear Uncertain Systems

2019 ◽  
Author(s):  
Jingting Zhang ◽  
Chengzhi Yuan ◽  
Paolo Stegagno
Keyword(s):  
Fault Detection ◽  
Discrete Time ◽  
Uncertain Systems ◽  
Adaptive Dynamics ◽  
Adaptive Threshold ◽  
Detection Methods ◽  
Detection Scheme ◽  
Uncertain Dynamics ◽  
Small Fault ◽  
Nonlinear Uncertain Systems

Abstract This paper addresses the problem of small fault detection for discrete-time nonlinear uncertain systems. The problem is challenging due to (i) the considered system is subject to unstructured nonlinear uncertain dynamics; and (ii) the faults are considered to be “small” in the sense that system states and control inputs in faulty mode remain close to those in normal mode. To overcome these challenges, a novel adaptive dynamics learning based fault detection scheme is proposed. Specifically, an adaptive dynamics learning approach is first proposed to achieve the locally-accurate approximation of the system uncertain dynamics. Then, based on the learned knowledge, a novel residual system is designed by using the absolute measures of the change of the system dynamics resulting from the fault effect. An adaptive threshold is developed based on the residual system for real-time decision making, i.e., the fault is claimed to be detected when the associated residual signal becomes larger than the adaptive threshold. Rigorous analysis is performed to deduce the small fault detectability condition, which is shown to be significantly relaxed compared to those of existing fault detection methods. Extensive simulations have also been conducted to demonstrate the effectiveness and advantages of the proposed approach.

Sign in / Sign up

Export Citation Format

Share Document