Kiln thermal and combustion control

• US 20040059441A1
• Filed: 09/23/2003
• Published: 03/25/2004
• Est. Priority Date: 05/06/1996
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Pavilion Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Piche, Stephen, Martin, Gregory D., Boe, Eugene, Havener, John P., Gerules, Mark, Timmer, Douglas, Keeler, James David
• Granted Patent: US 7,110,834 B2
• Time in Patent Office: Days
• US Class Current: 700/29
• CPC Class Codes: G05B 13/042 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: G05B 17/02 electric

Abstract

A kiln thermal and combustion control. A predictive model is provided of the dynamics of selected aspects of the operation of the system for modeling the dynamics thereof. The model has at least two discrete models associated therewith that model at least two of the selected aspects, the at least two discrete models having different dynamic responses. An optimizer receives desired values for the selected aspects of the operation of the system modeled by the model and optimizes the inputs to the model to minimize error between the predicted and desired values. A control input device then applies the optimized input values to the system

Claims

1. A controller for controlling a multi-variable input system having a plurality of manipulatible variables (MVs) as inputs, and operable to provide a plurality of measurable outputs and at least one unmeasurable output, which unmeasurable output can not be measured in substantially real time and requires external analysis for the determination of parameters thereof, comprising:

a system predictive model that provides a model of the dynamics of selected aspects of the operation of the system for modeling the dynamics thereof and providing at least one predicted output for at least a select one of the measurable outputs;

an external predictive model for receiving an external analysis of at least one parameter of the unmeasurable output and a desired unmeasurable output value for that at least one parameter, and the external predictive model operable to predict the dynamics of a select one of the measurable outputs as a function of the at least one parameter and the desired unmeasurable output value for the at least one parameter to predict the dynamics as a desired value of the select one of the measurable outputs required to achieve the desired unmeasurable output value;

an optimizer for receiving desired values for the selected aspects of the operation of the system modeled by said predictive model and said predicted outputs from said predictive model in addition to the desired value of the select one of the measurable outputs generated by said external predictive model and optimizing the inputs to the predictive model to minimize error between the predicted and desired values; and

a control input device for applying the optimized input values to the system after optimization thereof.

2. The controller of claim 1, wherein said optimizer is further operable to receive constraints on said input values such that the optimization operation changes the inputs within said constraints when minimizing the error between the predicted and desired values.

3. The controller of claim 1, wherein the system is subject to at least one disturbance variable that alters the operation of the system and wherein said predictive model will predict the behavior of the selected aspects modeled thereby in response to changes in the at least one disturbance variable and said optimizer will change the inputs to again minimize the error between the predicted and desired values.

7. The controller of claim 1, wherein said external predictive model comprises a linear model.

8. The controller of claim 1, wherein the unmeasurable output comprises a product that is fabricated by the system.

9. The controller of claim 1, wherein said optimizer is not operable to utilize said external predictive model during the operation thereof for the purpose of prediction therewith.

4. A method for controlling a multi-variable input system having a plurality of manipulatible variables (MVs) as inputs, and operable to provide a plurality of measurable outputs and at least one unmeasurable output, which unmeasurable output can not be measured in substantially real time and requires external analysis for the determination of parameters thereof, comprising the steps of:

providing a system predictive model that provides a model of the dynamics of selected aspects of the operation of the system for modeling the dynamics thereof and providing at least one predicted output for at least a select one of the measurable outputs;

providing an external predictive model for receiving an external analysis of the at least one parameter of the unmeasurable output and a desired unmeasurable output value for that at least one parameter, and the external predictive model operable to predict the dynamics of a select one of the measurable outputs as a function of the at least one parameter and the desired value for that at least one parameter to predict the dynamics as a desired value of the select one of the measurable outputs required to achieve the desired unmeasurable output value;

receiving in an optimizer desired values for the selected aspects of the operation of the system modeled by the predictive model and the predicted outputs from the predictive model in addition to the desired value of the select one of the measurable outputs generated by the external predictive model and optimizing the inputs to the predictive model to minimize error between the predicted and desired values; and

applying the optimized input values to the system after optimization thereof.

5. The method of claim 13, wherein the step of optimizing is further operable to receive constraints on the input values such that the optimization operation changes the inputs within the constraints when minimizing the error between the predicted and desired values.

6. The method of claim 13, wherein the system is subject to at least one disturbance variable that alters the operation of the system and wherein the predictive model will predict the behavior of the selected aspects modeled thereby in response to changes in the at least one disturbance variable and the step of optimizing will change the inputs to again minimize the error between the predicted and desired values.

10. The method of claim 13, wherein the external predictive model comprises a linear model.

11. The method of claim 13, wherein the unmeasurable output comprises a product that is fabricated by the system.

12. The method of claim 13, wherein the step of optimizing is not operable to utilize the external predictive model during the operation thereof for the purpose of prediction therewith.