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Inverse Simulation for Gas Turbine Engine Control through Differential Algebraic Inequality Formulation

  • Tarun Uppal EMAIL logo , Soumyendu Raha and Suresh Srivastava
Published/Copyright: November 8, 2018
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Abstract

Modern day gas turbines are prime movers in land, air and sea. They have stringent performance requirements to meet the complex mission objectives. Optimal control strategies can help them meet their performance objectives more efficiently. A novel inverse simulation method for optimal control and system analysis studies using Differential Algebraic Equality/Inequality (DAE/DAI) technique is brought out in this paper with a case study. The gas turbine model together with safety constraints and performance specifications is represented as a high index DAI/DAE system. The solution for this DAE/DAI system is obtained using a new numerical approach that is capable of handling both equality and inequality constraints on system dynamics. The algorithm involves direct numerical integration of a DAI formulation in a time stepping manner using Sequential Quadratic Programming (SQP) solver that detects and satisfy active constraints at each time step (mesh point). In this unique approach the model and the constraints are always solved together. The method ensures stable solution at each time step, local minimum at each iteration of simulation and provides a regularised basis to the solver. Compared to other existing computationally intensive techniques in usage, this approach is easy, ensures continuous constraint satisfaction and provides a viable option for Model Predictive Control (MPC) of gas turbine engines.

Symbols and notations

ωd

Damped natural frequency

ωn

Natural frequency

ρ

Alpha method tuning parameter-1

σ

Alpha method tuning parameter-2

ξ

Damping ratio

an

Value of acceleration term at step

an+1

Value of acceleration term at n+1th step

t

Time

t0

Start time

tf

Final timenth

u

Control vector

un+1

Value of control variables at n+1th step

x

State vector

x0

Initial start vector

xn+1

Value of state variables at n+1thstep

y

Output vector

A

Plant matrix

B

Control matrix

C

Output matrix

D

Direct transmission matrix

I/P

Input

N1

Low pressure spool speed

N2

High pressure spool speed

NozArea

Exhaust nozzle area

O/P

Output

P1

Ambient pressure

P2

Compressor inlet pressure

P3

Compressor discharge pressure

P5

Turbine pressure

P6

Exhaust pressure

P62

Mixer area pressure

T1

Ambient temperature

T6

Exhaust temperature

Wf

Main combustor fuel rate

Abbreviations
DAE

Differential Algebraic Equation

DAI

Differential Algebraic Inequality

GTE

Gas Turbine Engine

HPC

High Pressure Compressor

HPT

High Pressure Turbine

LPC

Low Pressure Compressor

LPT

Low Pressure Turbine

MIL-STD 5007E

Military Standard

MPC

Model Predictive Control

PID

Proportional Integral Derivative

PLA

Pilot Level Angle

ODE

Ordinary Differential Equation

SFC

Specific Fuel Consumption

SISO

Single Input Single Output

SQP

Sequential Quadratic Programming

VG

Variable Geometry

Acknowledgements

Authors are thankful to Director, Group Director and Divisional Head of flight mechanics and control engineering group of Aeronautical Development Establishment (ADE) for granting permission to publish this research work. Authors would also like to thank Shri.Sreenesh for helping with word processor for this manuscript.

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Received: 2016-08-14
Accepted: 2016-09-14
Published Online: 2018-11-08
Published in Print: 2018-12-19

© 2018 Walter de Gruyter GmbH, Berlin/Boston

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