Method for on-line optimization of a plant

• US 6,278,899 B1
• Filed: 10/06/1998
• Issued: 08/21/2001
• Est. Priority Date: 05/06/1996
• Status: Expired due to Term

• Current Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Original Assignee: Pavilion Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Piche, Stephen, Havener, John P., Semrad, Donald
• Primary Examiner(s): Grant, William
• Assistant Examiner(s): Marc, McDieunel, Marc, McDieunel
• Application Number:
  US09/167,504
• Time in Patent Office: 1,050 Days
• Field of Search: 700/269, 700/273, 700/288, 700/44, 375/316, 375/329, 375/350, 341/143, 329/318
• US Class Current: 700/44
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: G05B 17/02 electric

Abstract

An on-line optimizer is comprised of a nonlinear dynamic model (702) which is operable to provide an estimation of the output of a plant. This receives manipulated variables (MV), disturbance variables (DV), and computed disturbance variables (CDB). The estimated output of the model is then compared to the actual output measured by virtual on-line analyzer (VOA) (616). This is compared is a difference block 618 to generate a bias which is then filtered by a filter(620). The output thereof is then provided to an output block (672) in a steady state optimizer (700) to offset the desired setpoints. These set points are input to a steady state nonlinear model which is operable to optimize the inputs to the plants for use for writing new set points in accordance with a predetermined cost function. This cost function is utilized to optimize the new inputs with the use of the steady state model in accordance with various constraints and target values.

Claims

1. An on-line optimizer for optimizing operation of a plant with respect to predetermined operating parameters, comprising:

a steady state optimizer for modeling the operation of the plant and for receiving target plant output values and optimization criteria for generating plant input values that are optimized in accordance with the optimization criteria and with respect to predetermined operating parameters;

a nonlinear dynamic model for modeling the dynamics of the plant and providing estimated plant output values that constitute predicted values of the plant outputs;

an analyzer for providing a measurement of the real time and actual plant outputs during operation thereof;

a difference device for measuring the difference between the estimated output of said nonlinear dynamic model and the output of said difference circuit as a bias value; and

an offset device for offsetting the operation of said steady state optimizer by said bias value during on-line operation of the plant.

2. The on-line optimizer of claim 1, wherein said offset device is operable to offset the target plant output values by said bias value, which represents the difference between the estimated plant output values and the actual output values.

3. The on-line optimizer of claim 2, wherein said steady state optimizer and said nonlinear dynamic model utilize substantially the same model of the plant.

4. The on-line optimizer of claim 1, wherein said nonlinear model accounts for unmeasurable external disturbances.

5. The on-line optimizer of claim 1, and further comprising a smoothing device for filtering the output of said difference device.

6. The on-line optimizer of claim 1, wherein the output of said steady state optimizer provides estimated inputs to the plant is in an on-line mode such that said steady optimizer is a feedback relationship with the plant.

7. The on-line optimizer of claim 1, wherein said steady state optimizer includes a nonlinear model that is designed to store a representation of the gain of the plant and said nonlinear dynamic model is designed to provide an accurate prediction of the operation of the plant.

8. A nonlinear model for modeling operation of a plant, comprising:

an input layer for receiving a plurality of inputs, at least a predetermined number thereof defining a group of inputs;

an output layer;

a conversion device for mapping said group of inputs to a number of intermediate inputs less than the number in said group through a predefined relationship that defines a desired operating parameter of the plant based upon said group of inputs; and

a hidden layer for mapping the ones of said inputs not in said group and said intermediate inputs through a stored representation of said plant to said output layer.

9. The model of claim 8, wherein said number of said intermediate inputs comprises one.

10. The model of claim 8, wherein said predefined relationship is a linear relationship.

11. The model of claim 8, wherein said predefined relationship comprises an empirical relationship.

12. A method for optimizing operation of a boiler, comprising the steps of:

measuring the inputs and the outputs of the plant;

mapping a defined plurality of the measured inputs through a predetermined relationship that defines a desired operating parameter of the plant based upon said defined plurality of the measured inputs to intermediate inputs numbering less than the defined plurality of the measured inputs;

processing the intermediate inputs and the inputs not in said defined plurality of the measured inputs through a steady state optimizer to provide optimized intermediate input values for the intermediate inputs and optimized inputs not in the defined plurality of the measured inputs;

mapping the optimized intermediate input values through an inverse of the predetermined relationship to provide an optimized defined plurality of inputs corresponding to the defined plurality of the measured inputs; and

applying the optimized defined plurality of inputs and the optimized inputs not in the defined plurality of the measured inputs to the plant.

13. The method of claim 12, wherein the boiler has a furnace with a plurality of inlet ports for providing fuel to a desired location in the furnace and arranged at different elevations, such that fuel can selectively be delivered at various of the elevations at different feed rates, and wherein the predetermined relationship comprises:

$\mathrm{Fe}=\frac{\left(K_1\right)<br><br>\left(R_1\right)+\left(K_2\right)<br><br>\left(R_2\right)+\left(K_3\right)<br><br>\left(K_4\right)<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{\dots <br><br>}+\left(K_n\right)<br><br>\left(R_n\right)}{R_1+R_2+R_3<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{\dots <br><br>}+R_n}$

where;

Fe=Calculated Fuel Elevation

K₁ . . . K_n=Elevation Constant for elevation 1 to n (described hereinbelow)

R₁ . . . R_n=Coal Feed Rate for elevation 1 to n

such that fuel can be concentrated at a desired location in the furnace with a desired center of mass for the fuel concentration.