Research Papers: Gas Turbines: Structures and Dynamics

Fault Tolerant Control of an Industrial Gas Turbine Based on a Hybrid Fuzzy Adaptive Unscented Kalman Filter

[+] Author and Article Information
Amin Mirzaee

e-mail: amin_mirzae@yahoo.com

Karim Salahshoor

e-mail: salahshoor@put.ac.ir
Department of Instrumentation and
Industrial Automation,
Petroleum University of Technology,
Ahwaz 63431, Iran

1Corresponding author.

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received December 27, 2012; final manuscript received June 23, 2013; published online September 20, 2013. Assoc. Editor: Allan Volponi.

J. Eng. Gas Turbines Power 135(12), 122501 (Sep 20, 2013) (13 pages) Paper No: GTP-12-1496; doi: 10.1115/1.4025309 History: Received December 27, 2012; Revised June 23, 2013

Gas turbines are generally used in power generation, the oil and gas industries, and as jet engines in aircrafts. Fault tolerance and reliability is important in such applications. Thus, accurate modeling and control system design is necessary. In this paper, first a nonlinear hybrid fuzzy model was developed for an industrial gas turbine, and then this model was used as the core of a fault tolerant control (FTC) system. The aforementioned model was trained by use of three months of operational data of a GE MS 5002 D gas turbine that is used for gas injection application, then it was fine tuned using expert knowledge and physical principles. A graphical user interface (GUI) was also developed to run various realistic operational scenarios of the gas turbine. The main point of the present work consists in introducing nonlinear fuzzy model schemes as the core of an adaptive unscented Kalman filter (AUKF) for fault diagnostic purposes. Analysis of the simulation results discloses that this FTC approach alleviates the effects of faults in two different scenarios such as sequential drift and bias in sensors/actuators and also in simultaneous faults that are a disastrous situation.

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Fig. 1

The schematic of a GE MS 5002 D two shaft gas turbine

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Fig. 2

A typical ANFIS model with two inputs and one output

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Fig. 4

The schematic diagram of a conventional decentralized gas turbine control system

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Fig. 3

The validation of the proposed hybrid nonlinear gas turbine model

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Fig. 5

The validation of a linear PEM model

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Fig. 7

Startup manipulated variables trends

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Fig. 8

Startup load trends

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Fig. 9

The performance of a centralized MPC based gas turbine control

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Fig. 10

The performance of a decentralized conventional PID based gas turbine control

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Fig. 11

The operation of a FSR selection algorithm

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Fig. 12

Fault estimation capability of a FDI module

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Fig. 13

Output trends of an AFTC system in the first fault scenario

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Fig. 14

Output trends of a conventional control system in the first fault scenario

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Fig. 15

Output trends of an AFTC system in the second fault scenario

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Fig. 16

Output trends of a conventional control system in the second fault scenario

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Fig. 17

Computation time of the CPU for the first fault scenario




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