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Title: Nonlinear model predictive control for chemical looping process

Abstract

A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to a CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.

Inventors:
; ;
Publication Date:
Research Org.:
GENERAL ELECTRIC TECHNOLOGY GMBH, Baden, CH (Switzerland)
Sponsoring Org.:
USDOE
OSTI Identifier:
1375942
Patent Number(s):
9,740,214
Application Number:
13/946,115
Assignee:
GENERAL ELECTRIC TECHNOLOGY GMBH NETL
DOE Contract Number:
FC26-07NT43095
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Jul 19
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Joshi, Abhinaya, Lei, Hao, and Lou, Xinsheng. Nonlinear model predictive control for chemical looping process. United States: N. p., 2017. Web.
Joshi, Abhinaya, Lei, Hao, & Lou, Xinsheng. Nonlinear model predictive control for chemical looping process. United States.
Joshi, Abhinaya, Lei, Hao, and Lou, Xinsheng. Tue . "Nonlinear model predictive control for chemical looping process". United States. doi:. https://www.osti.gov/servlets/purl/1375942.
@article{osti_1375942,
title = {Nonlinear model predictive control for chemical looping process},
author = {Joshi, Abhinaya and Lei, Hao and Lou, Xinsheng},
abstractNote = {A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to a CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Aug 22 00:00:00 EDT 2017},
month = {Tue Aug 22 00:00:00 EDT 2017}
}

Patent:

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  • A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may includemore » difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.« less
  • A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may includemore » difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.« less
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  • A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with onemore » or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.« less
  • A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with onemore » or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.« less