Analog Control Module Templates

Inside this topic

CASCADE_MASTER Module Template
CASCADE_SLAVE Module Template
PID_LOOP Module Template
FLC_LOOP Module Template
FF_PID_LOOP Module Template
PID_DEADTIME Module Template
PID_GAINSCHED Module Template
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CASCADE_MASTER Module Template

The CASCADE_MASTER template has a PID function block and seven alarm parameters (High, Low, and PV Bad are enabled as a default). It also includes a module block representing the module created from the CASCADE_SLAVE module template.

After the slave loop module has been edited, create the master loop module from CASCADE_MASTER. The procedure for customizing the master loop module is similar to that of the slave loop with one added step: the module block on the master loop's function block diagram must be converted to point to the actual slave loop module rather than to the CASCADE_SLAVE library template. To convert the module, follow these steps:

1. Select the module block.
2. Click the right mouse button.
3. Click Convert to Existing Object from the menu.
4. Browse for the slave loop module you created from CASCADE_SLAVE. You might want to rename the module block to match the tag of the slave loop module, but this is optional.

The execution rate for the module created from CASCADE_MASTER is 2 seconds by default, and the slave module created from CASCADE_SLAVE defaults to 0.5 seconds.

Quick Config Parameters for CASCADE_MASTER

CASCADE_SLAVE Module Template

CASCADE_SLAVE is a module template similar to the PID_LOOP template. It includes several module level connection parameters for communication with the module created from the CASCADE_MASTER template. All seven alarm parameters in CASCADE_SLAVE are disabled as a default.

When the module library is used to create a cascade control strategy, a module must be created from each of two module templates, CASCADE_MASTER and CASCADE_SLAVE. Start with CASCADE_SLAVE.

Quick Config Parameters for CASCADE_SLAVE

PID_LOOP Module Template

PID_LOOP is a module template that consists of a PID function block and seven alarm parameters for HighHigh, High, Low, LowLow, DeviationHigh, DeviationLow, and PV Bad alarms. Initially, only the High, Low, and PV Bad alarms are enabled in PID_LOOP. Others can be enabled as needed.

The PID_LOOP module template has a single PID function block. The PID block has IO Reference parameters for the process variable input and control output. In most cases, you do not need to add additional function blocks to the module for a simple PID loop. But if, for example, your process variable is calculated or selected from several analog inputs, you can add this logic to the module after it is created from the template. You might need to add function blocks for feedforward control or tracking. The control output variable, IO_OUT, is typically a Device Signal Tag that specifies a Device Tag on an analog output channel and parameter. It could also be a discrete output channel (continuous pulse output) if you are doing time proportional output control.

Quick Config Parameters for PID_LOOP

Note that MODE is not a Quick Config parameter. The initial target mode for the PID function block in all of the analog control module templates is Manual. There might be other parameters that you need to configure that are not in the Quick Config view. If so, set the parameter filtering to Common Configuration (or Common Configuration and Advanced Configuration) to review or change other parameter values.

FLC_LOOP Module Template

FLC_LOOP is a module template that consists of an FLC (Fuzzy Logic Control) function block and seven alarm parameters for HighHigh, High, Low, LowLow, DeviationHigh, DeviationLow, and PV Bad alarms. Initially, only the High, Low, and PV Bad alarms are enabled in FLC_LOOP. Others can be enabled as needed.

The FLC_LOOP module template has a single FLC function block. The FLC block has IO Reference parameters for the process variable input and control output. In most cases, you do not need to add additional function blocks to the module for a simple FLC loop. But if, for example, your process variable is calculated or selected from several analog inputs, you can add this logic to the module after it is created from the template. You might need to add function blocks for feedforward control or tracking. The control output variable, IO_OUT, is typically a Device Signal Tag that specifies a Device Tag on an analog output channel and parameter.

Quick Config Parameters for FLC_LOOP

Note that MODE is not a Quick Config parameter. The initial target mode for the FLC function block is Manual. There might be other parameters that you need to configure that are not in the Quick Config view. If so, set the parameter filtering to Common Configuration (or Common Configuration and Advanced Configuration) to review or change other parameter values.

FF_PID_LOOP Module Template

This module is intended to be used for control in the field, that is, when the control algorithm runs in fieldbus devices. The AI block is to be assigned to a transmitter and the AO block to a valve. The PID block can be assigned to either a transmitter or valve.

This module template is similar to PID_LOOP, the primary difference being that three function blocks are used instead of one. Both templates share the same dynamos in !Modules. Use either the PID LOOP 1 or PID LOOP 2 dynamo on your control display.

There are a few differences in the faceplate and detail display used by the two templates. The faceplates look identical, but the fieldbus faceplate bases the output indication fields on OUT of the AO function block rather than OUT_READBACK of the PID block. On both faceplates data entry for the output is written to the PID block OUT. Note that the OUT value field on the PID LOOP 1 dynamo is linked to OUT_READBACK of the PID block.

Another difference between the two faceplates is the rectangular button that appears next to the output value field in the fieldbus faceplate. This button is white when the target mode of the AO block is Cas (its normal mode). When the button is clicked, the target mode is changed to Auto which causes a value field to appear directly below the button. This value field is for the setpoint of the AO block. The button is cyan when the target mode of the AO block is Auto. Clicking the button again causes the target mode to change back to Cas and the setpoint value field to disappear. The button becomes white. This button is on the faceplate in the event that the PID block is in a transmitter that becomes unavailable. The AO block in the valve can still be manipulated in this event.

The detail displays of the two templates differ in some of the parameters shown, due to the differences in parameters in the DeltaV controller PID block and fieldbus device PID block.

Quick Config Parameters for FF_PID_LOOP

PID_DEADTIME Module Template

This PID loop module uses a modified Smith Predictor for PID control with deadtime compensation. Use this module template if your self-regulating process is deadtime dominant, that is, its deadtime is about the same or greater than the process time constant.

Theory of Operation

With a Smith Predictor, the control actions are calculated based on the predicted process response to a change, with and without the deadtime. The Smith Predictor first models the process as a first-order equation without deadtime. The predicted process variable is calculated and sent to the PID block as a pseudo-process variable.

To compensate for the disturbances in the process, the actual process variable with deadtime is added to the feedback loop. The Smith Predictor calculates the model error by taking the difference between the actual process variable and the model process variable. After it calculates the model error, a Smith Predictor adjusts the model bias according to the magnitude of the disturbance. The following figure contains a representation of the Smith Predictor control.

Smith Predictor Control Scheme

This text so far has explained a standard Smith Predictor, but the DeltaV PID_DEADTIME module uses a modified Smith Predictor . In addition to the capability of the standard Smith Predictor, the modified Smith Predictor can adjust the model gain instead of the model bias, if the primary process disturbances are proportional in nature. The following figure shows the change in the output caused by a disturbance when a bias correction is needed versus when a model gain correction is needed. You must decide which correction is best for your process based on the type of disturbances you have. For example, a disturbance in the feed temperature of a heat exchanger does not change the process gain, it merely results in a bias to the heat required to maintain the outlet temperature. However, a disturbance in the feed rate to that heat exchanger results in a change in the process gain. If the more significant disturbance is feed temperature, use Bias as the correction type. If feed rate is the more significant disturbance, use Gain as the correction type.

Selecting Model BIAS vs. Model GAIN

If the model process variable with deadtime accurately reflects the actual process, the model output cancels the process feedback signal. Under these conditions, the closed loop characteristics are only a function of the PID block and the process model without deadtime. The control is improved because deadtime is eliminated from the feedback signal used for control.

Model error and process disturbances can cause the model process variable with deadtime to deviate from the actual process. The modified Smith Predictor allows you to limit the amount of model error correction provided. The error correction limit should be set greater than the contribution of the typical disturbance to the process measurement, yet small enough to protect against potential instrumentation problems.

The following figure shows a representation of the modified Smith Predictor with model BIAS and correction limiting.

Modified Smith Predictor with BIAS for Model Correction

The following figure shows a representation of the modified Smith Predictor with model GAIN and correction limiting.

Modified Smith Predictor with GAIN for Model Correction

Configuration

To configure a PID with deadtime compensation module, create a module from the module template PID_DEADTIME using the DeltaV Explorer. You can use the DeltaV Explorer or Control Studio to customize the module's properties and configuration parameters. There are configuration tips in the function block diagram of the module in Control Studio. Refer to the Quick Configuration Parameter table below for PID_DEADTIME.

Enter the process model parameters (model GAIN, model TIMECONST, and model DEAD_TIME) if they are already known. If not, they can be entered from the detail display in DeltaV Operate after you have done the open-loop step testing. Because the module uses a modified Smith Predictor, you must also configure the CORRECTION type you want for your process disturbances (model GAIN or model BIAS) and the correction LIMIT.

Note that the I/O Reference parameter for the process variable input is configured using IO_IN in the AI function block, not in the PID block.

Scaling information for the process variable must be entered in three parameters, AI1/OUT_SCALE, PID1/PV_SCALE, and SCLR1/OUT_SCALE. Typically, the value of the fields in all three parameters should be the same. However, an offset can be applied to EU0 and EU100 in SCLR1/OUT_SCALE if there is model offset at steady state when SCLR1/OUT_SCALE has the same values as AI1/OUT_SCALE and PID1/PV_SCALE. In some processes the relationship between the PID output and the process output is linear but has a fixed offset. This means that at steady state the correction term that is calculated by subtracting the predicted process variable from the actual contains this offset value. This causes a problem when a model limit is applied that is similar to or smaller than the offset. If necessary, set the offset in EU0 and EU100 to be the same as the process offset so the value of the correction term is 0 at steady state.

Use the following guidelines when you configure alarm condition parameters in this module. Configure the alarm hysteresis value and the HI, HI_HI, LO, and LO_LO limit values in the AI function block. Configure the deviation limit parameters in the PID function block.

The PID_DEADTIME module template supports variable deadtime compensation. You can improve the control performance if the process deadtime is variable and can be calculated, for example, as a function of the process throughput. Calculate the actual process deadtime in another control module and write the value to the DEAD_TIME parameter in the DTC composite block in your deadtime compensation module.

PID_DEADTIME Quick Config Parameters

Quick Config Parameters for PID_DEADTIME

To configure DeltaV Operate for this module, place the PID DT COMP dynamo on your control display. The faceplate and detail display names are pre-defined as module properties. The faceplate is essentially the same as the standard PID loop faceplate. The PV field is from the AI function block rather than the PID block because the PID block PV is the pseudo-PV when deadtime compensation is enabled. The detail display is unique for modules created from the deadtime compensation module template. For more information on the specific detail display, refer to the PID DT Comp detail display topic.

Tuning the Modified Smith Predictor

When tuning the modified Smith Predictor, you first must identify a first order plus deadtime model of your process. You can use Tune with InSight or perform a manual step test to develop the model. If you are using Tune's On-demand or Adaptive tuning  to develop the model, disable DT Comp and use Tune for On-demand Tuning or enable Process Learning for Adaptive Tuning to identify the first order plus deadtime process model.

Optionally, you can perform one or more open loop step tests to determine the gain, time constant, and deadtime of the process. The values must be accurate to within 25 percent of the actual process values. Apply model parameters (for example, deadtime, time constant, and gain to the DT Compensator).

Do not update the PID controller with PID parameters provided by Tune. Instead, use one of the following methods:

• Enable DT Comp and run InSight again. Use PI selections only. Update PID with new tuning results.
•  

  or

   
• Calculate the PID parameters as instructed below.

After you enter the deadtime compensation parameters, setting the PID block tuning parameters is straightforward. With deadtime compensation enabled, the loop is tuned as if the process is without deadtime. Only set the GAIN and RESET values in the PID block for a loop with deadtime compensation. Set the RATE to 0.

Configure RESET to be equal to the model TIMECONST value. PID block GAIN can be adjusted to get the desired closed loop response. The initial PID block GAIN can be set as a function of the model GAIN. Setting the PID block GAIN equal to the inverse of the model GAIN (PID GAIN = 1 / model GAIN) results in a closed loop time constant equal to the open loop time constant. Make sure that the closed loop time constant is longer than the open loop time constant to reduce sensitivity to model error. Therefore, reduce the initial PID block GAIN by 30 percent or more (PID GAIN = 0.7 / model GAIN).

PID_GAINSCHED Module Template

This PID loop module provides for scheduling of GAIN, RESET, and RATE based on the value of a process input within a three-region range. Tuning parameters are specified for each region. The PID block parameters are calculated from the process input, two limit values that define the boundary between regions, and a deadband value used to interpolate between regions for smooth transitions. The process input is selected to be either the PV or OUT of the PID block or an auxiliary variable.

Theory of Operation

PID control with gain scheduling is used to reduce the effect of process nonlinearity on the control loop's performance. The approach used here assumes the process is nonlinear, but has linear behavior within each of two or three process regions. Within each region pre-defined PID tuning parameter settings (GAIN, RESET, and RATE) are used. The PID settings are switched automatically when the process moves into a different region. To prevent abrupt changes to PID settings and subsequent process bumps, the gain scheduler uses an interpolation range between regions to provide smooth transitions. Within the interpolation range, the PID settings are calculated using a linear interpolation of the configured settings for the adjacent regions.

Interpolation Regions with Deadbands at the Limits

Configuration of the gain scheduler module includes defining the process input used to determine the state of the process, that is, where the process currently is operating within its range. The process input can be the PV or OUT of the PID block or an auxiliary variable. An example of when to choose the PV as the reference variable is pH control. The process curve of a pH control loop has the highest gain in the middle region based on the actual pH. The gain may be one or two orders of magnitudes higher than the gain in the lower and upper region. An example of when to use OUT as the reference value is for a temperature control loop with split range control for heating and cooling. An auxiliary variable would be used as a reference, for example, when the process nonlinearity is a function of process throughput. The auxiliary variable measures the current process throughput in this case.

Configuration of the gain scheduler module includes defining the interface points, called LIMIT1 and LIMIT2, between three regions of linearity. Set the limits at points where the PID settings need to change most drastically. The settings used within a region are configured using a manual or automatic tuning procedure. The control module monitors the process and uses the settings you establish for that region. If the process requires only two regions of linearity, set one of the limit values to the far end of the process range.

Use the interpolator to make the change in PID settings more gradual between regions. If the gain characteristics of the loop change over a wide range, the interpolation range between regions may be larger. If the process characteristics change quickly at one point, the interpolation range should be small. The interpolation range is determined by a single DEADBAND parameter that is applied to both limit values. The interpolation range is defined by the limit value plus and minus one-half of the deadband value.

Note The value of the DEADBAND parameter must be greater than zero.

Configuration

To configure a gain scheduling module, create a module from the module template PID_GAINSCHED using the DeltaV Explorer. You can use the DeltaV Explorer or Control Studio to customize the module's properties and configuration parameters. Note that you must use Control Studio if you want to use an auxiliary variable as the reference variable. If so, create an external reference parameter for the variable using an Internal Read special item and wire it into IN3 of the MLTX1 block. 

As an alternative, the gain scheduling module can be configured from the detail display in DeltaV Operate if you have the Tuning and Restricted Control privilege.

Use either of the standard PID module dynamos, PID LOOP 1 or PID LOOP 2 for a gain scheduling module. The faceplate for the gain scheduling module is the standard PID faceplate, but the detail display is unique to the gain scheduler. The faceplate and detail display names are predefined as module properties.