Robust adaptive model predictive controller with tuning to compensate for model mismatch
First Claim
1. A method of tuning a model predictive controller for use in controlling a process, comprising:
- obtaining via a computer processor a process model for the process, the process model including a value for each of a set of process model parameters;
obtaining via a computer processor a process model mismatch indication identifying a process model mismatch for at least one of the set of process model parameters; and
performing on a computer processor a controller optimization based on the process model and the process model mismatch indication including determining a control-based performance measure for the model predictive controller when operated using each of a multiplicity of different sets of controller design/tuning parameter values and the process model in presence of an amount of process model mismatch associated with the process model mismatch indication, and determining an optimal one of the set of the controller design/tuning parameter values for use in the model predictive controller based on the control-based performance measures.
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Abstract
An MPC adaptation and tuning technique integrates feedback control performance better than methods commonly used today in MPC type controllers, resulting in an MPC adaptation/tuning technique that performs better than traditional MPC techniques in the presence of process model mismatch. The MPC controller performance is enhanced by adding a controller adaptation/tuning unit to an MPC controller, which adaptation/tuning unit implements an optimization routine to determine the best or most optimal set of controller design and/or tuning parameters to use within the MPC controller during on-line process control in the presence of a specific amount of model mismatch or a range of model mismatch. The adaptation/tuning unit determines one or more MPC controller tuning and design parameters, including for example, an MPC form, penalty factors for either or both of an MPC controller and an observer and a controller model for use in the MPC controller, based on a previously determined process model and either a known or an expected process model mismatch or process model mismatch range. A closed loop adaptation cycle may be implemented by performing an autocorrelation analysis on the prediction error or the control error to determine when significant process model mismatch exists or to determine an increase or a decrease in process model mismatch over time.
145 Citations
52 Claims
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1. A method of tuning a model predictive controller for use in controlling a process, comprising:
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obtaining via a computer processor a process model for the process, the process model including a value for each of a set of process model parameters; obtaining via a computer processor a process model mismatch indication identifying a process model mismatch for at least one of the set of process model parameters; and performing on a computer processor a controller optimization based on the process model and the process model mismatch indication including determining a control-based performance measure for the model predictive controller when operated using each of a multiplicity of different sets of controller design/tuning parameter values and the process model in presence of an amount of process model mismatch associated with the process model mismatch indication, and determining an optimal one of the set of the controller design/tuning parameter values for use in the model predictive controller based on the control-based performance measures. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29)
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30. An adaptive model predictive controller for use in controlling a process plant, comprising:
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a model predictive controller unit having a controller model and one or more alterable design/tuning parameters; and a tuning unit including; a model storage that stores a process model for the process plant, the process model specifying a value for each of a set of process model parameters; and an optimization unit communicatively coupled to the model predictive controller, wherein the optimization unit simulates the operation of the model predictive controller in the presence of a non-zero process model mismatch when the controller model is based on the process model, for each of a plurality of simulation instances, wherein during each simulation instance, the model predictive controller is configured with a different set of controller design/tuning parameter values, the optimization unit determining a controller performance measure for each of the simulation instances, the optimization unit further determining an optimal one of the sets of controller design/tuning parameter values for use in the model predictive controller based on the controller performance measures. - View Dependent Claims (31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45)
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46. An adaptive model predictive controller tuning unit for implementation on a computer processor to tune a model predictive controller that operates to control a process plant using a controller model, comprising:
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a non-transitory computer readable medium; a storage routine stored on the computer readable medium for execution on a processor to store a process model for the process plant, the process model specifying a value for each of a set of process model parameters; and an optimization routine stored on the computer readable medium for execution on a processor to simulate the operation of the model predictive controller in presence of a process model mismatch when the controller model of the model predictive controller is based on the process model, the optimization routine simulating the model predictive controller when the model predictive controller is configured with each of a plurality of different sets of controller design/tuning parameter values, the optimization routine determining a controller performance measure for each of the plurality of different sets of controller design/tuning parameter values in the presence of the process model mismatch, and the optimization routine still further determining an optimal one of the different sets of controller design/tuning parameter values for use in the model predictive controller based on the controller performance measures. - View Dependent Claims (47, 48, 49, 50, 51, 52)
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Specification