NDLI: Fuzzy indirect adaptive control using SVM-based multiple models for a class of nonlinear systems

Content Provider	Springer Nature Link
Author	Zhou, Yonghua
Copyright Year	2012
Abstract	Adaptive control with multiple models can further improve the adaptation ability of controllers for the plant with wide-range uncertain parameters. Fuzzy modeling and control are introduced into the multiple-model adaptive control in this paper, which facilitates the intelligent behavior of a plant facing with uncertainty. Within the combination of fuzzy sets of state variables, the corresponding combined kernel functions of support vector machine are utilized to describe the unknown nonlinear dynamics. The coefficients of kernel functions are learned online through adaptive laws. The multiple identification models and indirect adaptive controllers are assigned to the plant through fuzzy inferences. The stability of adaptive law corresponding to the fuzzy identification model and the synthetic control input through fuzzy fusion has been proved for the proposed fuzzy multiple-model adaptive control (FMMAC). The simulation results demonstrate that the proposed FMMAC can achieve favorable control performance for a class of nonlinear systems.
Starting Page	825
Ending Page	833
Page Count	9
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	22
Issue Number	3-4
e-ISSN	14333058
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-12-30
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Fuzzy control Support vector machine Adaptive learning Indirect adaptive control Multiple models Nonlinear system Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science Computational Science and Engineering Image Processing and Computer Vision Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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

A rough margin-based one class support vector machine

Hierarchical fuzzy CMAC control for nonlinear systems

Multiple birth support vector machine for multi-class classification

Multiclass Lagrangian support vector machine

An adaptive class pairwise dimensionality reduction algorithm

A fast fuzzy support vector machine based on information granulation

Wavelet twin support vector machine

Fuzzy rules extraction from support vector machines for multi-class classification

Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation

Fuzzy indirect adaptive control using SVM-based multiple models for a class of nonlinear systems

Similar Documents

A rough margin-based one class support vector machine

Hierarchical fuzzy CMAC control for nonlinear systems

Multiple birth support vector machine for multi-class classification

Multiclass Lagrangian support vector machine

An adaptive class pairwise dimensionality reduction algorithm

A fast fuzzy support vector machine based on information granulation

Wavelet twin support vector machine

Fuzzy rules extraction from support vector machines for multi-class classification

Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation

Fuzzy indirect adaptive control using SVM-based multiple models for a class of nonlinear systems