NDLI: New SISO and MISO Adaptive Nonlinear Predictive Controllers based on self organizing RBF neural networks

Content Provider	IEEE Xplore Digital Library
Author	Kamalabady, A.S. Salahshoor, K.
Copyright Year	2008
Description	Author affiliation: Dept. of Autom. & Instrum., Pet. Univ. of Technol., Tehran (Kamalabady, A.S.; Salahshoor, K.)
Abstract	This paper proposes an adaptive nonlinear model predictive control (NMPC) scheme for control of nonlinear time-varying processes. An online identification approach based on an adaptive modified growing and pruning radial basis function (MGAP-RBF) neural network is presented to model the process dynamics in real-time operations using an unscented Kalman filtering (UKF) estimation algorithm with a forgetting factor scheme. A single-input, single-output (SISO) adaptive NMPC controller is described based on quasi-Newton approach. The adaptive NMPC control procedure is extended to multi-input, single-output (MISO) processes. The proposed SISO and MISO NMPC controllers are evaluated on a highly non-linear time- varying nonisothermal continuous stirred tank reactor (CSTR) benchmark problem. The simulation results demonstrate the potential capabilities of the two developed NMPC controllers to identify and control the CSTR process with superior performance over the conventional PID controller.
Starting Page	703
Ending Page	708
File Size	453389
Page Count	6
File Format	PDF
ISBN	9781424416875
DOI	10.1109/ISCCSP.2008.4537314
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-12
Publisher Place	Malta
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filtering Adaptive filters Predictive models Adaptive NMPC Adaptive control Organizing MGAP-RBF Programmable control UKF Online identification SISO Neural networks Continuous-stirred tank reactor Kalman filters MISO Predictive control
Content Type	Text
Resource Type	Article

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

New SISO and MIMO Adaptive Generalized Predictive Controllers based on Self-Organizing RBF Neural Networks

An adaptive integral plus states neural control of aerobic continuous stirred tank reactor

Model predictive control with state estimation and adaptation mechanism for a continuous stirred tank reactor

Adaptive nonlinear control of continuously stirred tank reactor systems

Non-linear State Estimation for Continuous Stirred Tank Reactor using Neural Network State Filter

A new Fault Toletant Nonlinear Model Predictive Controller based on an adaptive extended kalman filter

Adaptive model predictive control of a hybrid motorboat using self-organizing GAP-RBF neural network and GA algorithm

On-line multivariable identification by adaptive RBF neural networks based on UKF learning algorithm

Nonlinear continuous stirred tank reactor (CSTR) identification and control using recurrent neural network trained Shuffled Frog Leaping Algorithm

New SISO and MISO Adaptive Nonlinear Predictive Controllers based on self organizing RBF neural networks

Similar Documents

New SISO and MIMO Adaptive Generalized Predictive Controllers based on Self-Organizing RBF Neural Networks

An adaptive integral plus states neural control of aerobic continuous stirred tank reactor

Model predictive control with state estimation and adaptation mechanism for a continuous stirred tank reactor

Adaptive nonlinear control of continuously stirred tank reactor systems

Non-linear State Estimation for Continuous Stirred Tank Reactor using Neural Network State Filter

A new Fault Toletant Nonlinear Model Predictive Controller based on an adaptive extended kalman filter

Adaptive model predictive control of a hybrid motorboat using self-organizing GAP-RBF neural network and GA algorithm

On-line multivariable identification by adaptive RBF neural networks based on UKF learning algorithm

Nonlinear continuous stirred tank reactor (CSTR) identification and control using recurrent neural network trained Shuffled Frog Leaping Algorithm

New SISO and MISO Adaptive Nonlinear Predictive Controllers based on self organizing RBF neural networks