NDLI: The new method of flatness pattern recognition based on GA–RBF

Content Provider	Springer Nature Link
Author	Zhang, Xiu Ling Cheng, Long Hao, Shuang Gao, Wu Yang Lai, Yong Jin
Copyright Year	2015
Abstract	Radial basis function (RBF) network combines with AutoRegressive eXogenous (ARX) model to create RBF–ARX model. RBF–ARX model can describe the global nonlinear dynamic process of the object, and its function coefficients are approximated by data-driven method. Structured nonlinear parameters optimization method is generally used to optimize model parameters, but this method is very complicated and hard to be mastered by engineers. However, genetic algorithm (GA) is relatively simple and widely used. So thought of GA optimizing RBF–ARX is generated, called GA–ARX–RBF, and applied to nonlinear dynamic flatness recognition model. Flatness pattern recognition is the basis and core of flatness control. Considering disadvantages of traditional pattern recognition method, such as limitation of recognition accuracy and poor fault tolerance, a new intelligent method of flatness pattern recognition based on the GA–RBF–ARX model is proposed. Meanwhile, in order to examine the effectiveness of RBF–ARX, another intelligent flatness recognition model based on dynamic feedback Hopfield NN is set up. Simulation proves that RBF–ARX is more suitable for flatness pattern recognition than Hopfield NN. And optimization effect by GA can achieve the desired requirements and is more precise than structured nonlinear parameters optimization method, when RBF–ARX is applied to rolling mill. GA–RBF–ARX can be a new modeling method for complex nonlinear dynamic system.
Starting Page	1535
Ending Page	1548
Page Count	14
File Format	PDF
ISSN	0924090X
Journal	Nonlinear Dynamics
Volume Number	83
Issue Number	3
e-ISSN	1573269X
Language	English
Publisher	Springer Netherlands
Publisher Date	2015-10-13
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Flatness pattern recognition RBF–ARX model Genetic algorithm Hopfield NN Vibration, Dynamical Systems, Control Mechanics Mechanical Engineering Automotive Engineering
Content Type	Text
Resource Type	Article
Subject	Ocean Engineering Applied Mathematics Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Aerospace Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Pattern Recognition and Synchronization in Pulse-Coupled Neural Networks

Dynamic analysis of unstable Hopfield networks

A differential flatness theory approach to observer-based adaptive fuzzy control of MIMO nonlinear dynamical systems

Pattern Formation of Dunes

A Wavelet-Balance Method to Investigate the Vibrations of Nonlinear Dynamical Systems

Differential-flatness-based finite-time anti-swing control of underactuated crane systems

An Alternate Method to the Alternating Time-Frequency Method

An ℋ$_{∞}$ approach to stability analysis of switched Hopfield neural networks with time-delay

Optimal design of multi-parametric nonlinear systems using a parametric continuation based Genetic Algorithm approach

The new method of flatness pattern recognition based on GA–RBF–ARX and comparative research

Similar Documents

Pattern Recognition and Synchronization in Pulse-Coupled Neural Networks

Dynamic analysis of unstable Hopfield networks

A differential flatness theory approach to observer-based adaptive fuzzy control of MIMO nonlinear dynamical systems

Pattern Formation of Dunes

A Wavelet-Balance Method to Investigate the Vibrations of Nonlinear Dynamical Systems

Differential-flatness-based finite-time anti-swing control of underactuated crane systems

An Alternate Method to the Alternating Time-Frequency Method

An ℋ$_{∞}$ approach to stability analysis of switched Hopfield neural networks with time-delay

Optimal design of multi-parametric nonlinear systems using a parametric continuation based Genetic Algorithm approach

The new method of flatness pattern recognition based on GA–RBF–ARX and comparative research