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Multivariable optimal control of an industrial nonlinear boiler–turbine unit

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Abstract

Performance control of a boiler–turbine unit is of great importance due to demands for the economical operations of power plants and environmental awareness. In this paper, an optimal control strategy is designed to achieve the desired performance of a boiler–turbine unit. A multivariable nonlinear model of a utility boiler–turbine unit is considered. By manipulation of valves position for the fuel, steam and feed-water flows; output variables including the drum pressure, electric output and fluid density (and consequently drum water level) are controlled. Performance measure of the problem is defined such that the control efforts are minimized while the tracking objectives are obtained. In development of the optimal control strategy, the “variation of extremal” approach is used as an effective tool to handle the nonlinear uncertain problems. Tracking performance of the system is investigated and compared for three cases; tracking from a specific operating point to another ‘near’, ‘far’ and ‘farther’ operating point (depending on the distance between the operating points, the qualitative phrases ‘near’, ‘far’ and farther’ are used). According to the results obtained, more control efforts are required for the tracking of farther operating points (generally). Also, it is investigated that the designed optimal controller guarantees the robust performance of the system in the presence of model parametric uncertainties.

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Abbreviations

\( {\bar{\mathbf{a}}} \) :

Nonlinear function in state space

a cs :

Steam quality

\( H_{\infty } \) :

H-infinity robust technique

H :

Hamiltonian function

I :

Identity matrix

J :

Performance measure (objective function)

p i :

i-th Component of P (i = 1, 2, 3)

P :

Co-state vector

\( {\tilde{\mathbf{P}}}_{{\mathbf{x}}} \) :

State influence matrix

\( {\tilde{\mathbf{P}}}_{{\mathbf{p}}} \) :

Co-state influence matrix

q e :

Evaporation rate (kg/s)

q i :

i-th Component of Q (i = 1, 2, 3)

Q :

A real symmetric positive semi-definite matrix

r i :

i-th Component of R (i = 1, 2, 3)

R :

A real symmetric positive definite matrix

t :

Time (s)

t 0 :

Initial time

t f :

Final time

u 1 :

Valve position of fuel flow

u 2 :

Valve position of steam control

u 3 :

Valve position of feed-water flow

\( u_{i}^{*} \) :

Optimal control signals in terms of state and co-state variables (i = 1, 2, 3)

U :

Control input vector

x i :

i-th State variable

X :

State vector

X d :

Desired state vector

y 1 :

Drum pressure (kg f/cm2) (y 1 = x 1)

y 2 :

Electric output (MW) (y 2 = x 2)

y 3 :

Fluid density (kg/m3) (y 3 = x 3)

y 4 :

Drum water level (m)

\( y_{i}^{(j)} \) :

Output y i at the operating point # j

δ :

Parameter taking a small value

\( \psi_{i} \) :

A nonlinear function (i = 1, 2)

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Acknowledgments

The authors acknowledge the ‘National Elite Foundation of Iran’ for supporting this research.

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Correspondence to Hamed Moradi.

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Appendix

Appendix

Using Eq. (6), coefficients of state and co-state influence matrices (\( {\tilde{\mathbf{P}}}_{{\mathbf{x}}} \) and \( {\tilde{\mathbf{P}}}_{{\mathbf{p}}} \)) in Eq. (12) are evaluated as:

$$ \begin{aligned} \left[ {\frac{{\partial^{2} {\mathbf{H}}}}{\partial P\partial X}} \right] & = \left[ {\begin{array}{lll} {0.0020\,x_{1}^{{{1 \mathord{\left/ {\vphantom {1 8}} \right. \kern-0pt} 8}}} \,\psi_{1} + 0.0018\,x_{1}^{{{9 \mathord{\left/ {\vphantom {9 8}} \right. \kern-0pt} 8}}} \,\psi_{2} } \hfill & 0 \hfill & 0 \hfill \\ { - 0.0821\,x_{1}^{{{1 \mathord{\left/ {\vphantom {1 8}} \right. \kern-0pt} 8}}} \,\psi_{1} - 0.073\,x_{1}^{{{9 \mathord{\left/ {\vphantom {9 8}} \right. \kern-0pt} 8}}} \,\psi_{2} - 0.018\,x_{1}^{{{1 \mathord{\left/ {\vphantom {1 8}} \right. \kern-0pt} 8}}} } \hfill & { - 0.1} \hfill & 0 \hfill \\ {0.01294\,(\psi_{1} + x_{1} \,\psi_{2} ) + 0.00223} \hfill & 0 \hfill & 0 \hfill \\ \end{array} } \right] = \left[ {\frac{{\partial^{2} {\mathbf{H}}}}{\partial X\partial P}} \right]^{T} \\ \left[ {\frac{{\partial^{2} {\mathbf{H}}}}{{\partial P^{2} }}} \right] & = - \left[ {\begin{array}{lll} {\frac{0.405}{{r_{1} }} + \frac{{1.62 \times 10^{ - 6} }}{{r_{2} }}x_{1}^{{{9 \mathord{\left/ {\vphantom {9 4}} \right. \kern-0pt} 4}}} + \frac{0.01125}{{r_{3} }}} \hfill & { - \frac{{6.57 \times 10^{ - 5} }}{{r_{2} }}x_{1}^{{{9 \mathord{\left/ {\vphantom {9 4}} \right. \kern-0pt} 4}}} } \hfill & {\frac{{1.16 \times 10^{ - 5} }}{{r_{2} }}x_{1}^{{{{17} \mathord{\left/ {\vphantom {{17} 8}} \right. \kern-0pt} 8}}} - \frac{0.1244}{{r_{3} }}} \hfill \\ {sym.} \hfill & {\frac{0.00266}{{r_{2} }}x_{1}^{{{9 \mathord{\left/ {\vphantom {9 4}} \right. \kern-0pt} 4}}} } \hfill & { - \frac{{4.72 \times 10^{ - 4} }}{{r_{2} }}x_{1}^{{{{17} \mathord{\left/ {\vphantom {{17} 8}} \right. \kern-0pt} 8}}} } \hfill \\ {sym.} \hfill & {sym.} \hfill & {\frac{{8.372 \times 10^{ - 5} }}{{r_{2} }}x_{1}^{2} + \frac{1.376}{{r_{3} }}} \hfill \\ \end{array} } \right]_{\text{symmetric}} \\ \left[ {\frac{{\partial^{2} {\mathbf{H}}}}{{\partial X^{2} }}} \right] & = \left[ {\begin{array}{lll} {2\,(q_{1} - \,r_{2} \psi_{2}^{2} ) + \psi_{1} \,\psi_{3} - 0.00225\,p_{2} \,x_{1}^{{ - {7 \mathord{\left/ {\vphantom {7 8}} \right. \kern-0pt} 8}}} } \hfill & 0 \hfill & 0 \hfill \\ 0 \hfill & {2\,q_{2} } \hfill & 0 \hfill \\ 0 \hfill & 0 \hfill & {2\,q_{3} } \hfill \\ \end{array} } \right] \\ \end{aligned} $$
(16)

where,

$$ \psi_{3} = \left( {2.531 \times 10^{ - 4} p_{1} - 0.01026p_{2} } \right)x_{1}^{ - 7/78.8} $$
(17)

and ψ 1ψ 2 are given by Eqs. (9) and (10).

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Moradi, H., Vossoughi, G. Multivariable optimal control of an industrial nonlinear boiler–turbine unit. Meccanica 51, 859–875 (2016). https://doi.org/10.1007/s11012-015-0259-0

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