Iterative system and process with non-linear correction factors

1. A system for solving a process problem comprising:

a process module comprising a storage memory device having stored thereon processor executable instructions for defining an iterative process having variables having certain values which, when applied to the iterative process, converge the iterative process to a solution and having other values which, when applied to the iterative process, do not converge the iterative process to a solution;

a process definition interface for receiving process input data defining a particular iterative process corresponding to the process problem and for providing the received process input data to the process module;

a variables interface for receiving variables input data defining values for the variables of the iterative process and for providing the received variables input data to the process module;

a non-linear corrector factor module comprising a storage memory device having stored thereon processor executable instructions for defining a non-linear correction factor to be applied to the variables of the iterative process;

a processor connected to the process module for executing the processor executable instructions stored on the process module according to the process input data received by the process definition interface, according to the variables input data received by the variables interface and applying the non-linear correction factor as defined by the non-linear correction factor module to provide a solution to the particular iterative process; and

a correction factor interface configured to present a user with an option to select at least two non-linear corrector factors wherein the non-linear correction factors include:

a non-linear correction factor defined by multiple lines having different slopes; and

a non-linear correction factor defined by a curved line provided by the user.

2. The system of claim 1 wherein the correction factor interface receives correction factor slope parameters from the user and provides the received correction factor slope parameters to the non-linear correction factor module and wherein the non-linear corrector factor module uses the received correction factor slope parameters to specify a different slope for each of the multiple lines.

3. The system of claim 1 wherein the processor executable instructions for defining an iterative process stored on the process module implement three alternative modes of operation to solve the process problem: (1) a “simulation” mode in which the problem is defined by a set of nonlinear equations; (2) a “data reconciliation” mode in which the problem is defined as a least squares optimization problem; and (3) an “optimization” mode in which the problem is defined as a nonlinear optimization problem.

4. The system of claim 1 wherein the correction factor interface receives correction factor curve parameters from the user and provides the received correction factor curve parameters to the non-linear correction factor module and wherein the non-linear corrector factor module uses the received correction factor curve parameters to specify the curved line.

5. The system of claim 4 wherein the correction factor curve parameters define a sinusoidal curve.

6. A system for solving a process problem comprising:

a Rigorous On-line Modeling and Equation-based Optimization (ROMEO) module comprising a storage memory device having stored thereon processor executable instructions for defining an iterative process having certain variables which, when applied to the iterative process, converge the iterative process to a solution and having other variables which, when applied to the iterative process, do not converge the iterative process to a solution;

a process definition interface for receiving process input data defining a particular iterative process and for providing the received process input data to the process module;

a variables interface for receiving variables input data defining values for the variables of the iterative process and for providing the received variables input data to the ROMEO module;

a non-linear creep factor module comprising a storage memory device having stored thereon processor executable instructions for defining a non-linear creep factor to be applied to the variables of the iterative process; and

a processor connected to the ROMEO module for executing the processor executable instructions stored on the ROMEO module according to the process input data received by the process definition interface, according to the variables input data received by the variables interface and applying the non-linear creep factor as defined by the non-linear creep factor module to provide a solution to the particular iterative process,

wherein the non-linear creep factor is defined by an algorithm specified by a user via the variables interface, the algorithm inferring the number of iterations based on a quantity of the defined particular iterative process specified by the user such that the non-linear creep factor is applied adaptively and wherein the number of iterations is defined by a parameter of the process defined by the user.

7. The system of claim 6 wherein the processor executable instructions for defining an iterative process stored on the ROMEO module implement three alternative modes of operation to solve the process problem: (1) a “simulation” mode in which the problem is defined by a set of nonlinear equations; (2) a “data reconciliation” mode in which the problem is defined as a least squares optimization problem; and (3) an “optimization” mode in which the problem is defined as a nonlinear optimization problem.

8. The system of claim 6 wherein the iterations are repeated until a robustness measure meets a preset minimum.

9. The system of claim 8 wherein the robustness measure is computed in one or more of the following ways: (i) constraint-closure norm; (ii) cost-function moving in the right direction; (iii) smallest number of cut-backs of line-step; or (iv) a weighted sum of some or all these measures.

10. A system for solving a process problem comprising:

a process module comprising a storage memory device having stored thereon processor executable instructions for defining an iterative process having variables having certain values which, when applied to the iterative process, converge the iterative process to a solution and having other values which, when applied to the iterative process, do not converge the iterative process to a solution;

a process definition interface for receiving process input data defining a particular iterative process corresponding to the process problem and for providing the received process input data to the process module;

a variables interface for receiving variables input data defining values for the variables of the iterative process and for providing the received variables input data to the process module;

a non-linear corrector factor module comprising a storage memory device having stored thereon processor executable instructions for defining a non-linear correction factor to be applied to the variables of the iterative process;

a processor connected to the process module for executing the processor executable instructions stored on the process module according to the process input data received by the process definition interface, according to the variables input data received by the variables interface and applying the non-linear correction factor as defined by the non-linear correction factor module to provide a solution to the particular iterative process; and

a correction factor interface configured to present a user with an option to select at least three non-linear corrector factors wherein the non-linear correction factors include:

a non-linear correction factor defined by multiple lines having different slopes;

a non-linear correction factor defined by a curved line provided by the user; and

a non-linear adaptive correction factor defined by an algorithm inferring the number of iterations based on a quantity of the defined particular iterative process such that the non-linear correction factor is applied adaptively.

11. The system of claim 10 wherein the number of non-linear adaptive correction factor iterations is defined by a parameter of the process.

12. The system of claim 10 wherein the correction factor interface receives correction factor slope parameters from the user and provides the received correction factor slope parameters to the non-linear correction factor module and wherein the non-linear corrector factor module uses the received correction factor slope parameters to specify a different slope for each of the multiple lines.

13. The system of claim 10 wherein the correction factor interface receives correction factor curve parameters from the user and provides the received correction factor curve parameters to the non-linear correction factor module and wherein the non-linear corrector factor module uses the received correction factor curve parameters to specify the curved line.

14. The system of claim 13 wherein the correction factor curve parameters define a sinusoidal curve.

15. The system of claim 10 wherein the non-linear adaptive correction factor iterations are repeated until a robustness measure meets a preset minimum.

16. The system of claim 15 wherein the robustness measure is computed in one or more of the following ways: (i) constraint-closure norm; (ii) cost-function moving in the right direction; (iii) smallest number of cut-backs of line-step; or (iv) a weighted sum of some or all these measures.

17. The system of claim 10 wherein the processor executable instructions for defining an iterative process stored on the process module implement three alternative modes of operation to solve the process problem: (1) a “simulation” mode in which the problem is defined by a set of nonlinear equations; (2) a “data reconciliation” mode in which the problem is defined as a least squares optimization problem; and (3) an “optimization” mode in which the problem is defined as a nonlinear optimization problem.