Filtering algorithm for delayed nonlinear systems with random deception attacks

2022 ◽  
Author(s):  
D. Dorathy Prema Kavitha ◽  
L. Francis Raj
Keyword(s):  
Nonlinear Systems ◽  
Filtering Algorithm

scholarly journals Strong Tracking Filtering Algorithm of Randomly Delayed Measurements for Nonlinear Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Hongtao Yang ◽  
Huibin Gao ◽  
Xin Liu
Keyword(s):  
Nonlinear Systems ◽  
Initial Conditions ◽  
Stochastic Dynamic ◽  
Model Simplification ◽  
Filtering Algorithm ◽  
First Order ◽  
Noise Characteristics ◽  
Delayed Measurements ◽  
Fading Factor ◽  
Stochastic Dynamic Systems

This paper focuses on the filtering problems of nonlinear discrete-time stochastic dynamic systems, such as the model simplification, noise characteristics uncertainty, initial conditions uncertainty, or system parametric variation. Under these circumstances, the measurements of system have one sampling time random delay. A new method, that is, strong tracking filtering algorithm of randomly delayed measurements (STF/RDM) for nonlinear systems based on recursive operating by analytical computation and first-order linear approximations, is proposed; a principle of extended orthogonality is presented as a criterion of designing the STF/RDM, and through the residuals between available and predicted measurements, the formula of fading factor is obtained. Under the premise of using the extended orthogonality principle, STF/RDM proposed in this paper can adjust the fading factor online via calculating the covariance of residuals, and then the gain matrices of the STF/RDM adjust in real time to enhance the performance of the proposed method. Lastly, in order to prove that the performance of STF/RDM precedes existing EKF method, the experiment of tracking maneuvering aircraft is carried out.

Identification of Continuous-time Nonlinear Systems via Local Gaussian Process Models

2014 ◽  
Vol 134 (11) ◽  
pp. 1708-1715
Author(s):  
Tomohiro Hachino ◽  
Kazuhiro Matsushita ◽  
Hitoshi Takata ◽  
Seiji Fukushima ◽  
Yasutaka Igarashi
Keyword(s):  
Nonlinear Systems ◽  
Gaussian Process ◽  
Continuous Time ◽  
Process Models ◽  
Gaussian Process Models

Modeling of Nonlinear Systems using Genetic Algorithm

2012 ◽  
Vol 132 (6) ◽  
pp. 913-918 ◽  
Author(s):  
Kayoko Hayashi ◽  
Toru Yamamoto ◽  
Kazuo Kawada
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Systems
Sign in / Sign up

Export Citation Format

Share Document