System and method of adaptive control of processes with varying dynamics
First Claim
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1. A process controller comprising:
- controller variable inputs comprised of measurements of process variable inputs of the process being controlled, wherein the process variable inputs include at least one manipulated variable, and wherein said at least one manipulated variable comprises a magnetic field strength, shape, location and/or orientation within a particle accelerator;
a dynamic predictive model of the process being controlled, with one or more dynamic predictive model parameters for receiving current variable input values, wherein the one or more dynamic predictive model parameters change dependent on said variable input values received by the controller; and
one or more outputs from the dynamic model for generating controller outputs for effectuating change to variable outputs of the process being controlled, wherein said variable outputs comprise particle positions within the particle accelerator.
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Abstract
The present invention provides a method for controlling nonlinear process control problems. This method involves first utilizing modeling tools to identify variable inputs and controlled variables associated with the process, wherein at least one variable input is a manipulated variable. The modeling tools are further operable to determine relationships between the variable inputs and controlled variables. A control system that provides inputs to and acts on inputs from the modeling tools tunes one or more manipulated variable inputs to achieve a desired result like greater efficiency, higher quality, or greater consistency.
87 Citations
38 Claims
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1. A process controller comprising:
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controller variable inputs comprised of measurements of process variable inputs of the process being controlled, wherein the process variable inputs include at least one manipulated variable, and wherein said at least one manipulated variable comprises a magnetic field strength, shape, location and/or orientation within a particle accelerator; a dynamic predictive model of the process being controlled, with one or more dynamic predictive model parameters for receiving current variable input values, wherein the one or more dynamic predictive model parameters change dependent on said variable input values received by the controller; and one or more outputs from the dynamic model for generating controller outputs for effectuating change to variable outputs of the process being controlled, wherein said variable outputs comprise particle positions within the particle accelerator. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A process control system comprising:
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a distributed control system that comprises; a computing device operable to execute a first software tool that identifies variable inputs including at least one manipulated variable input, and controlled variables associated with the process, wherein said first software tool is further operable to determine relationships between said variable inputs and said controlled variables; and at least one controller operable to monitor said variable inputs and tune said at least one manipulated variable input; wherein said at least one manipulated variable input comprises a strength, shape, location and/or orientation of a magnetic field in a particle accelerator, and said controlled variables comprise particle positions within the particle accelerator. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
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24. A dynamic process controller comprising:
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a dynamic predictive model for receiving variable input values of a process, wherein the variable input values include at least one manipulated variable value, and wherein said at least one manipulated variable value comprises a magnetic field strength, shape, location and/or orientation value within a particle accelerator, wherein said dynamic predictive model changes dependent upon said variable input values and controlled variable output values of the process, wherein said controlled variable output values comprise particle positions within the particle accelerator, and wherein said dynamic predictive model is used to produce a plurality of desired manipulated variable input values at different time positions between a first time and a second time to define a dynamic operation path of the process between controlled variable output values of the process at the first time and desired controlled variable output values of the process at the second time; and an optimizer for optimizing the plurality of desired manipulated variable input values in accordance with a predetennined optimization method that optimizes the dynamic operation path in accordance with the changing dynamic predictive model. - View Dependent Claims (25)
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26. A method for controlling operating process, comprising the steps of:
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identifying one or more variable inputs comprising a strength, shape, location and/or orientation of a magnetic field in a particle accelerator, and one or more controlled variables comprising particle positions within the particle accelerator, wherein at least one of said variable inputs is a manipulated variable; determining relationships between said one or more variable inputs and said one or more controlled variables, wherein said relationship comprises models, and wherein parameters within said models are dependent on value said one or more variable inputs; and tuning said at least one manipulated variable to achieve a desired controlled variable value. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38)
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Specification