A multiple model adaptive control (MMAC) methodology is used to control the critical parameters of a solid oxide fuel cell gas turbine (SOFC-GT) cyberphysical simulator, capable of characterizing 300 kW hybrid plants. The SOFC system is composed of a hardware balance of plant (BoP) component, and a high fidelity FC model implemented in software. This study utilizes empirically derived transfer functions (TFs) of the BoP facility to derive the MMAC gains for the BoP system, based on an estimation algorithm which identifies current operating points. The MMAC technique is useful for systems having a wide operating envelope with nonlinear dynamics. The practical implementation of the adaptive methodology is presented through simulation in the matlab/simulink environment.

Issue Section:
Research Papers
Topics:
Adaptive control, Algorithms, Control equipment, Gas turbines, Power stations, Probability, Solid oxide fuel cells, Transfer functions, Turbines, Actuators, Signals, Simulation, Flow (Dynamics)

References

1.
Tucker
,
D.
,
Lawson
,
L.
, and
Gemmen
,
R.
,
2003
, “
Preliminary Results of a Cold Flow Test in a Fuel Cell Gas Turbine Hybrid Simulation Facility
,”
ASME
Paper No. GT2003-38460
.
2.
Tucker
,
D.
,
Liese
,
E.
, and
Gemmen
,
R.
,
2009
, “
Determination of the Operating Envelope for a Direct Fired Fuel Cell Turbine Hybrid Using Hardware Based Simulation
,” International Colloquium on Environmentally Preferred Advanced Power Generation, Newport Beach, CA, Feb. 10–12, Paper No. ICEPAG2009-1021.
3.
Tucker
,
D.
, and
Gemmen, L. Lawson
,
R.
,
2005
, “
Characterization of Air Flow Management and Control in a Fuel Cell Turbine Hybrid Power System Using Hardware Simulation
,”
ASME
Paper No. PWR2005-50127
.
4.
Winkler
,
W.
,
Nehter
,
P.
,
Tucker
,
D.
,
Williams
,
M.
, and
Gemmen
,
R.
,
2006
, “
General Fuel Cell Hybrid Synergies and Hybrid System Testing Status
,”
J. Power Sources
,
159
(
1
), pp.
656
–
666
.
Google Scholar
Crossref
Search ADS
 
5.
Williams
,
M. C.
,
Strakey
,
J.
, and
Surdoval
,
W.
,
2006
, “
U.S. DOE Fossil Energy Fuel Cells Program
,”
J. Power Sources
,
159
(
2
), pp.
1241
–
1247
.
Google Scholar
Crossref
Search ADS
 
6.
Pezzini
,
P.
,
Banta
,
L.
,
Traverso
,
A.
, and
Tucker
,
D.
,
2014
, “
Decentralized Control Strategy for Fuel Cell Turbine Hybrid Systems
,”
57th Annual ISA Power Industry Division Symposium
, Scottsdale, AZ, June 1–6, Paper No. POWID2014-52.
7.
Pezzini
,
P.
,
Celestin
,
S.
, and
Tucker
,
D.
,
2015
, “
Control Impacts of Cold-Air Bypass on Pressurized Fuel Cell Turbine Hybrids
,”
ASME J. Fuel Cell Sci. Technol.
,
12
(
1
), p.
011006
.
Google Scholar
Crossref
Search ADS
 
8.
Tsai
,
A.
,
Banta
,
L.
,
Tucker
,
D.
, and
Gemmen
,
R.
,
2010
, “
Multivariable Robust Control of a Simulated Hybrid Solid Oxide Fuel Cell Gas Turbine Plant
,”
ASME J. Fuel Cell Sci. Technol.
,
7
(
4
), p.
041008
.
Google Scholar
Crossref
Search ADS
 
9.
Tsai
,
A.
,
Tucker
,
D.
, and
Groves
,
C.
,
2010
, “
Improved Controller Performance of Selected Hybrid SOFC-GT Plant Signals Based on Practical Control Schemes
,”
ASME J. Eng. Gas Turbines Power
,
133
(
7
), p.
071702
.
Google Scholar
Crossref
Search ADS
 
10.
Tucker
,
D.
,
Lawson
,
L.
,
Smith
,
T.
, and
Haynes
,
C.
,
2006
, “
Evaluation of Cathodic Air Flow Transients in a Hybrid System Using Hardware Simulation
,”
ASME
Paper No. FUELCELL2006-97107
.
11.
Tucker
,
D.
,
Ford
,
J.
,
Haynes
,
C.
,
VanOsdol
,
J.
,
Liese
,
E.
, and
Lawson
,
L.
,
2012
, “
Evaluation of Methods for Thermal Management in a Coal Based SOFC Turbine Hybrid Through Numerical Simulation
,”
ASME J. Fuel Cell Sci. Technol.
,
9
(
4
), p.
041004
.
Google Scholar
Crossref
Search ADS
 
12.
Traverso
,
A.
,
Tucker
,
D.
, and
Haynes
,
C.
,
2012
, “
Preliminary Experimental Results of Integrated Gasification Fuel Cell Operation Using Hardware Simulation
,”
ASME J. Eng. Gas Turbines Power
,
134
(
7
), p.
071701
.
Google Scholar
Crossref
Search ADS
 
13.
Tucker
,
D.
,
Smith
,
T.
, and
Lawson
,
L.
,
2006
, “
Characterization of Bypass Control Methods in a Coal Based Fuel Cell Turbine Hybrid
,”
ASME
Paper No. ICEPAG2006-24008
.
14.
Zhou
,
N.
,
Yang
,
C.
,
Tucker
,
D.
,
Pezzini
,
P.
, and
Traverso
,
A.
,
2005
, “
Transfer Function Development for Control of a Fuel Cell Turbine Hybrid System
,”
Int. J. Hydrogen Energy
,
40
(
4
), pp.
1967
–
1979
.
Google Scholar
Crossref
Search ADS
 
15.
Tsai
,
A.
,
Banta
,
L.
,
Tucker
,
D.
, and
Lawson
,
L.
,
2009
, “
Determination of an Empirical Transfer Function of a Solid Oxide Fuel Cell Gas Turbine Hybrid System Via Frequency Response Analysis
,”
ASME J. Fuel Cell Sci. Technol.
,
6
(
3
), p.
034505
.
Google Scholar
Crossref
Search ADS
 
16.
Chang
,
C.
, and
Athans
,
M.
,
1978
, “
State Estimation for Discrete Systems With Switching Parameters
,”
IEEE Trans. Aerosp. Electron. Syst.
,
AES-14
(
3
), pp.
418
–
425
.
Google Scholar
Crossref
Search ADS
 
17.
Narendra
,
K. S.
, and
Xiang
,
C.
,
2000
, “
Adaptive Control of Discrete-Time Systems Using Multiple Models
,”
IEEE Trans. Autom. Control
,
45
(
9
), pp.
1669
–
1686
.
Google Scholar
Crossref
Search ADS
 
18.
Athans
,
M.
,
1977
, “
The Stochastic Control of the F-8C Aircraft Using a Multiple Model Adaptive Control (MMAC) Method—Part I: Equilibrium Flight
,”
IEEE Trans. Autom. Control
,
AC-22
(
5
), pp.
768
–
780
.
Google Scholar
Crossref
Search ADS
 
19.
Tsai
,
A.
,
Tucker
,
D.
, and
Emami
,
T.
,
2016
, “
Multiple Model Adaptive Estimation of a Hybrid Solid Oxide Fuel Cell Gas Turbine Plant Simulator
,”
ASME
Paper No. FUELCELL2016-59656.
20.
Lewis
,
F.
,
1992
,
Applied Optimal Control and Estimation, Digital Design and Implementation
,
Prentice Hall
,
Englewood Cliff, NJ
.
21.
Franklin
,
G. F.
,
Powell
,
J. D.
, and
Workman
,
M. L.
,
1998
,
Digital Control of Dynamic Systems
, 3rd ed.,
Addison Wesley Longman, Inc., Menlo Park, CA
.
Copyright © 2019 by ASME
You do not currently have access to this content.