In some DeltaV installations, historical data can be collected and recorded either manually or from a system that is not connected to the DeltaV system. In other installations, historical data may have been saved in the historian of another control system that is being replaced by the DeltaV system. In these cases, it may save time to use this historical data, rather than data from the Continuous Historian, to create process models and control definitions to be used by the MPCPro of MPCPlus function blocks in a DeltaV system. The PredictPro application can use data from a file to develop the process model. The PredictPro application can also verify the process model against data from a file. This section describes how DeltaV PredictPro uses data files, the required data file format, and the utilities included in the DeltaV system to export data from the Continuous Historian into a file.
Developing a Process Model from File
The DeltaV PredictPro application normally uses data from the Continuous Historian to create the process model. However, DeltaV PredictPro can also use historical data saved in data files. The data file must contain historical values for all inputs and outputs used in the MPCPro or MPCPlus block and the data must be formatted correctly to be used by DeltaV PredictPro. Refer to Data File Format for more information.
To use historical data from a file, you must first create a module that contains an MPCPro or MPCPlus function block. The block must reference the DeltaV inputs and outputs that will be used in the control. Download the module to a controller or Application Station, start DeltaV PredictPro, and connect DeltaV PredictPro to the MPCPro or MPCPlus block. From DeltaV PredictPro, select , and autogenerate or create the model.
When you select either of these options, a dialog appears in which you specify the data file to use. After you select the data file and click OK, DeltaV PredictPro performs the selected command using the data file and presents the results as if you had used data from the Continuous Historian.
Verifying a Process Model against data from a File
In order to validate the identified process model, the DeltaV PredictPro application normally uses trend data from the Continuous Historian or the original data used to create the model. However, DeltaV PredictPro can also use historical data saved in data files. The data file must contain historical values for all inputs and outputs used in the MPCPro or MPCPlus block and the data must be formatted correctly to be used by DeltaV PredictPro. Refer to Data File Format for more information.
To verify a process against historical data from a file, you must have created a model for the configured MPCPro or MPCPlus function block, and you must be in Expert mode. In DeltaV PredictPro, select the model you want to validate and then either right-click and select or click the Verify button on the model display. When you select either of these options, a dialog appears in which you specify the data file to use. After you select the file and click OK, DeltaV PredictPro verifies the model predictions against the data file and presents the results as if you had used data from the Continuous Historian.
Data File Format
For best results when creating and verifying models from data files, the values contained in the data file should reflect normal conditions over the operating range of the process. For model creation, the data is normally of the form obtained with open loop bump testing. Any input or output sample values that represent abnormal conditions should be replaced by a non-numeric string in the data file. Use a tool such as Microsoft Excel to format and edit the file.
The data files must be saved as .dat files and formatted in a particular way for DeltaV PredictPro to use them. The data files must contain the following information formatted as described:
Line 1 - Must contain the phrase DeltaV_MPC_Pro_Data <eol>
The above header specifies to DeltaV Predict that this is a historical data file.
Line 2 - Lists the Number of Controlled and Constraint Variables<tab>The Number of Disturbance and Manipulated Variables<eol>
The number of variables should correspond to those that you configured in the associated MPCPro function block. Refer to the Example PredictPro Data File in this topic for an example.
Line 3 - Lists the Number of samples in the file <tab> The sampling period in seconds <eol>
The sampling period must be the sampling period of the data in the file.
Line 4 - The date in MM/DD/YYYY format <tab> Time in HH:MM:SS format for the last sample<eol>
Line 5 - An empty line <eol>
Line 6 - Lists the identifiers of the Control and Constraint followed by Manipulated and Disturbance references separated by tabs <eol>
The user configured identifier names such as FC201 should match those that you configured in the associated MPCPro or MPCPlus function block. They should be placed in the order of the variables as identified in the function block configuration (for example, Proc_Out1, Proc_Out2, Proc_In1, and so on). Therefore, the order will match that of the data, as indicated in Line 8.
Line 7 - An empty line <eol>
Line 8 through the end of data - The data in the following order: index of the sample<tab>first process output variable value<tab>… last Process ouput variable value<tab>first process input variable value<tab>… last process input variable value <eol>
The order of the data should match the order of the configured variables. If the data contains values that do not reflect normal operating conditions, replace those values with non-numeric strings to indicate that these values should not be used in the model identification. During identification, the corresponding sample values are replaced by interpolating between the good data values.
Last Line - An empty line <eol>
The following is an example PredictPro data file for a block consisting of four Controlled variables and five Constraint variables (totaling nine process outputs), and four Manipulated variables and two Disturbance variables (totaling six process inputs). The example shows only a portion of the starting and ending input and output values out of the 1618 total. The data was obtained with a sampling period of 1.0 seconds. Note that to flag some of the output and input data values as bad, (the values should be replaced by BAD, or any non-numeric string).
