In recent years the idea of artificial intelligence has been focused around the concept of rational agent. An agent is an (software or hardware) entity that can receive signals from the environment and act upon that environment through output signals, trying to carry out an appropriate task. Seldom agents are considered as stand-alone systems; on the contrary, their main strength can be found in the interaction with other agents, constituting the so-called multiagent system. In the present work, a multiagent system was chosen as a control system of a single-shaft heavy-duty gas turbine in the multi input multi output mode. The shaft rotational speed (power frequency) and stack temperature (related to the overall gas turbine efficiency) represent the controlled variables; on the other hand, the fuel mass flow (VCE) and the variable inlet guide vanes (VIGV) have been chosen as manipulating variables. The results show that the multiagent approach to the control problem effectively counteracts the load reduction (including the load rejection condition) with limited overshoot in the controlled variables (as other control algorithms do) while showing a good level of adaptivity, readiness, precision, robustness, and stability.

1.
Daniele
,
C. J.
, and
Krosel
,
S. M.
, 1979, “
Generation of Linear Dynamic Models From a Digital Nonlinear Simulation
,” NASA Technical Paper No. 1388, NASA.
2.
Smith
,
D. L.
, and
Stammetti
,
V. A.
, 1990, “
Sequential Linearization as an Approach to Real-Time Marine Gas Turbine Simulation
,”
J. Eng. Gas Turbines Power
0742-4795,
112
, pp.
187
191
.
3.
Dambrosio
,
L.
,
Camporeale
,
S. M.
, and
Fortunato
,
B.
, 2000, “
Performance of Gas Turbine Power Plants Controlled by One Step Ahead Adaptive Technique
,” ASME Paper No. GT-2000-037.
4.
Dambrosio
,
L.
, and
Fortunato
,
B.
, 1999, “
One-Step-Ahead Adaptive Control of a Wind-Driven, Synchronous Generator System
,”
Energy
0360-5442,
24
, pp.
9
20
.
5.
Goodwin
,
G. C.
, and
Sin
,
K. S.
, 1984,
Adaptive Filtering Prediction and Control
,
Prentice-Hall
, Englewood Cliffs, NJ.
6.
Dambrosio
,
L.
,
Camporeale
,
S. M.
, and
Fortunato
,
B.
, 2002, “
Control of Gas Turbine Power Plants by Means of the Weighted One Step Ahead Adaptive Technique
,”
Proc. Inst. Mech. Eng. Part I–Journal of System and Control Engineering
,
216
, pp.
317
324
.
7.
Zawia
,
S. M.
, and
Al-Khodari
,
M. S. B.
, 2004, “
Dynamic Modeling and Self-Tuning Control of a Gas Turbine
,” ASME Paper No. GT-2004-53530.
8.
Mu
,
J.
, and
Rees
,
D.
, 2004, “
Nonlinear Model Predictive Control for Gas Turbine Engines
,” ASME Paper No. GT-2004-53146.
9.
Brunell
,
B. J.
,
Viassolo
,
D. E.
, and
Prasanth
,
R.
, 2004, “
Adaptation and Nonlinear Model Predictive Control of an Aircraft
,” ASME Paper No. GT-2004-53780.
10.
Dambrosio
,
L.
,
Pascazio
,
G.
, and
Fortunato
,
B.
, 2005, “
Fuzzy Logic Controller Applied to Variable Geometry Turbine Turbocharger
,”
Proc. Inst. Mech. Eng., Part D (J. Automob. Eng.)
0954-4070,
219
, pp.
1347
1360
.
11.
Martucci
,
A.
, and
Volponi
,
A. J.
, 2000, “
Fuzzy Fuel Flow Selection Logic for a Real Time Embedded Full Authority Digital Engine Control
,” ASME Paper No. 2000-GT-0046.
12.
Mu
,
J.
, and
Rees
,
D.
, 2003, “
Optimum Gain-Scheduling PID Controllers for Gas Turbine Engines Based on Narmax and Neural Network Models
,” ASME Paper No. GT-2003-38667.
13.
Vroemen
,
B. G.
,
van Essen
,
H. A.
,
van-Steenhoven
,
A. A.
, and
Kok
,
J. J.
, 1999, “
Nonlinear Model Predictive Control of a Laboratory Gas Turbine Installation
,”
J. Eng. Gas Turbines Power
0742-4795,
121
, pp.
629
634
.
14.
Martucci
,
A.
,
Fuller
,
J.
,
Dorobantu
,
E.
, and
Rahnamai
,
K.
, 2004, “
The Effect of Terminal Weight on the Prediction Horizon of a Gas Turbine Engine Using Model Predictive Control
,” ASME Paper No. GT2004-53009.
15.
Vlassis
,
N.
, 2003, “
A Concise Introduction to Multiagent Systems and Distributed
,”
AI Intelligent Autonomous Systems Informatics Institute
,
University of Amsterdam
.
16.
Russell
,
S. J.
, and
Norvig
,
P.
, 2003,
Artificial Intelligence: A Modern Approach
, 2nd ed.,
Prentice-Hall
, Englewood Cliffs, NJ.
17.
Mendel
,
J. M.
, 1995, “
Fuzzy Logic Systems for Engineering: A Tutorial
,”
Proc. IEEE
0018-9219,
83
, pp.
345
377
.
18.
Camporeale
,
S. M.
,
Fortunato
,
B.
, and
Mastrovito
,
M.
, 2002, “
A High Fidelity Real Time Simulation Code of Gas Turbine Dynamics for Control Applications
,” ASME Paper No. GT-2002-30039.
19.
El Mastri
,
M. A.
, 1988, “
On the Thermodynamics of Gas Turbines Cycles—Part II: A Model of Expansion in Cooled Turbines
,”
J. Eng. Gas Turbines Power
0742-4795,
110
, pp.
201
209
.
20.
Jansen
,
M.
,
Schulenberg
,
T.
, and
Waldinger
,
D.
, 1992, “
Shop Test Results for the v64.3 Gas Turbine
,”
J. Eng. Gas Turbines Power
0742-4795,
114
, pp.
676
681
.
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