APM.FILTER - APMonitor Option

Main.OptionApmFilter History

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June 09, 2017, at 12:03 AM by 10.5.113.159 -
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See also Estimation Objective Tuning

to:

See also FSTATUS, MEAS, Estimation Objective Tuning

June 05, 2017, at 09:18 PM by 10.5.113.159 -
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 (Model value) = (Model value) * (1-FILTER) + (Measured value) * FILTER
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 Model = Model * (1-FILTER) + Measured * FILTER
June 05, 2017, at 09:16 PM by 10.5.113.159 -
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FILTER determines how much of the raw measurement is used to update the value of MEAS. A filter of 0 indicates that the measurement should not be used in updating the MEAS value. A filter of 1.0 uses all of the measurement and ignores any prior measurement value and 0.5 uses half of each according to the formula: New Input = Current Value * (1-FILTER) + Raw Input * FILTER. The FILTER parameter applies to all inputs into the model from the CSV (data) file but not from the DBS (database) file. The FSTATUS parameter is used to adjust the fractional update from new measurements when using apm_meas(s,a,'name',value) to input measurements. Both FSTATUS and FILTER are useful to control the flow of information into the model. It is sometimes desirable to set FILTER or FSTATUS to a low value (close to 0) when the solver is not able to find a solution because of big input changes. A drawback of a filter on data is that raw inputs are not used in the application and it takes several cycles to reach true input values.

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FILTER determines how much of the raw measurement is used to update the value of MEAS. A filter of 0 indicates that the measurement should not be used in updating the MEAS value. The FILTER parameter applies to all inputs into the model from the CSV (data) file and also from the DBS (database) file. FILTER at 1.0 uses all of the measurement and ignores any prior measurement value and 0.5 uses half of each.

 CSV (data) file
 (Model value) = (Model value) * (1-FILTER) + (Measured value) * FILTER

 DBS (database) file
 MEAS =  MEAS * FILTER + LSTVAL * (1-FILTER)

The FSTATUS parameter is used to adjust the fractional update from new measurements when using apm_meas(s,a,'name',value) but this only applies to a single entity at a time. FILTER applies globally to all inputs. Both FSTATUS and FILTER are useful to control the flow of information into the model. It is sometimes desirable to set FILTER or FSTATUS to a low value (close to 0) when the solver is not able to find a solution because of big input changes. A drawback of a filter on data is that raw inputs are not used in the application and it takes several cycles to reach true input values.

June 05, 2017, at 09:10 PM by 10.5.113.159 -
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FILTER determines how much of the raw measurement is used to update the value of MEAS. A filter of 0 indicates that the measurement should not be used in updating the MEAS value. A filter of 1.0 uses all of the measurement and ignores any prior measurement value and 0.5 uses half of each according to the formula: New Input = Current Value * (1-FILTER) + Raw Input * FILTER. The FILTER parameter applies to all inputs into the model from the CSV (data) file but not from the DBS (database) file. The FSTATUS parameter is used to adjust the fractional update from new measurements when using apm_meas(s,a,'name',value) to input measurements.

to:

FILTER determines how much of the raw measurement is used to update the value of MEAS. A filter of 0 indicates that the measurement should not be used in updating the MEAS value. A filter of 1.0 uses all of the measurement and ignores any prior measurement value and 0.5 uses half of each according to the formula: New Input = Current Value * (1-FILTER) + Raw Input * FILTER. The FILTER parameter applies to all inputs into the model from the CSV (data) file but not from the DBS (database) file. The FSTATUS parameter is used to adjust the fractional update from new measurements when using apm_meas(s,a,'name',value) to input measurements. Both FSTATUS and FILTER are useful to control the flow of information into the model. It is sometimes desirable to set FILTER or FSTATUS to a low value (close to 0) when the solver is not able to find a solution because of big input changes. A drawback of a filter on data is that raw inputs are not used in the application and it takes several cycles to reach true input values.

June 05, 2017, at 08:28 PM by 10.5.113.159 -
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(:title FSTATUS - APMonitor Option:) (:keywords FSTATUS, Optimization, Estimation, Option, Configure, Default, Description:)

to:

(:title APM.FILTER - APMonitor Option:) (:keywords APM.FILTER, Optimization, Estimation, Option, Configure, Default, Description:)

June 05, 2017, at 08:27 PM by 10.5.113.159 -
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(:title FSTATUS - APMonitor Option:) (:keywords FSTATUS, Optimization, Estimation, Option, Configure, Default, Description:) (:description Measurement first-order filter: (0-1):)

 Type: Floating Point, Input
 Default Value: 1.0
 Description: Measurement first-order filter: (0-1)

FILTER determines how much of the raw measurement is used to update the value of MEAS. A filter of 0 indicates that the measurement should not be used in updating the MEAS value. A filter of 1.0 uses all of the measurement and ignores any prior measurement value and 0.5 uses half of each according to the formula: New Input = Current Value * (1-FILTER) + Raw Input * FILTER. The FILTER parameter applies to all inputs into the model from the CSV (data) file but not from the DBS (database) file. The FSTATUS parameter is used to adjust the fractional update from new measurements when using apm_meas(s,a,'name',value) to input measurements.

See also Estimation Objective Tuning