Change Operating Points

Switch between operating points during simulation

Since R2023b

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Libraries:
Simulink Control Design / Autotuning

Description

The Change Operating Points block lets you manage and switch operating points during simulation. You can use the block in one of these configurations:

• Import predefined operating data from workspace and switch between operating range during the simulation.

• Automatically snapshot at specified times or events during simulation to obtain the operating point data at the specified range. For example, for a motor model, you can snapshot at:

  • 3, 5, and 7 s (time-based).

  • 2000, 5000, and 8000 rpm (event-based).

When you have predefined operating point data, you can use this block in gain-scheduled controller tuning workflows. This block helps generate reference signals which move your plant from one operating point to another. Otherwise, snapshot the operating points first, and then use the data for gain scheduling workflows.

Typically, tuning a gain-scheduled controller is a complex process. It requires you to run multiple simulations for tuning at each operating point and provide a logic to store PID gains at that operating point. Using this block, along with the PID Gains Store and Update and PID Gain Scheduler blocks, helps you implement a streamlined workflow for autotuning gain-scheduled PID controllers over an operating range in a single run. To do so, use this workflow.

1. Switch between predefined or snapshot operating point data during the simulation using the Change Operating Points block.

2. Perform autotuning at the operating points using Closed-Loop PID Autotuner.

3. Store the PID gains corresponding to the operating point in an array using PID Gains Store and Update block.

4. Perform lookup table based gain scheduling from the array using the PID Gain Scheduler block.

On a high level, you can use these blocks to implement the gain-scheduled workflow as shown in this diagram.

Ports

Input

systeminputs_in — System inputs

array

Specify the value of the input level at the operating point.

When the block is operating in the snapshot mode, the block directly passes through this input to the systeminputs_out port.

enable/disable — Enable and disable changing operating points

scalar

Specify a signal to enable (1) or disable (0) the block action.

autotuning times — Time vector to start autotuning

vector

Specify the time vector to start autotuning. The value at each index of this vector is the autotuning start time for the operating point at that index. Use the Autotuning time span (sec) parameter to specify the duration of the experiment.

Dependencies

To enable this port, use this configuration.

• Set Operating mode to Import operating points.

• Select Use block for autotuning.

• Set Method for starting autotuning to External time vector.

next OP — Next operating point

scalar

Specify the custom logic to switch to the next operating point.

Dependencies

To enable this port, use this configuration.

• Set Operating mode to Import operating points.

• Set Transition method to External trigger.

y — Plant output

scalar | vector

Connect the output of your plant to this port. The block determines the current operating state of the system using this signal.

Dependencies

To enable this port, use this configuration.

• Set Operating mode to Import operating points.

• Select Use block for autotuning.

• Set Method for starting autotuning to Time after reaching steady-state.

enable autotuning — Enable or disable autotuning

scalar

Use this port to manually specify a scalar flag to enable (1) or disable (0) the autotuning process.

Dependencies

To enable this port, use this configuration.

• Set Operating mode to Import operating points.

• Select Use block for autotuning and Add enable/disable port for autotuning.

snapshot trigger — Snapshot trigger

vector

Specify the time-based or event-based snapshot triggers at which you want to extract the operating point of the model.

When Snapshot mode is Time-based, specify the time values for which you want to snapshot operating point data. For example, to snapshot at 3, 5, and 7 s, use a vector [3,5,7] as input to this port.

When Snapshot mode is Event-based, the block snapshots the operating point data at the rising edges of the input signal.

Dependencies

To enable this port, set Operating mode to Snapshot operating points, and use one of these configurations.

• Set Snapshot mode to Time-based and select Use external source.

• Set Snapshot mode to Event-based.

Output

systeminputs_out — Operating point output

bus

Reference signal to move the system to the switched operating point.

start_stop — Signal to start and stop the autotuning

scalar

Signal to start and stop the autotuning process with the Closed-Loop PID Autotuner block. The generated signal depends on the additional parameters such as the autotuning method and steady-state settings.

Dependencies

To enable this port, set Operating mode to Import operating points and select Use block for autotuning.

Parameters

Import operating point Tab

Operating mode — Mode for operating point data

Import operating points (default) | Snapshot operating points

Specify the mode for obtaining the operating point data.

• Import operating points — Specify predefined operating point data by either manually editing the table in block dialog or importing an OperatingPoint object.

  In this mode, you can use the block to implement a streamlined workflow for autotuning gain-scheduled PID controllers over an operating range.

• Snapshot operating points — Snapshot operating points at specified times or events during simulation.

Programmatic Use

Block Parameter: OperatingMode

Type: string

Values: "Import operating points" | "Snapshot operating points"

Default: "Import operating points"

Input method — Input method for operating point data

Manually edit table (default) | Automatically fill Table

Specify the input method for operating point data.

• Manually edit table — Manually specify the operating point data in the block dialog.

• Automatically fill table — Import operating point data using an OperatingPoint object. Typically, you obtain operating points using functions such as operpoint and findop, or Steady State Manager and Model Linearizer apps. You can also import the operating point data obtained using the snapshot mode of this block.

Dependencies

To enable this parameter, set Operating mode to Import operating points.

Programmatic Use

Block Parameter: InputMethod

Type: string

Values: "Manually edit table" | "Automatically fill table"

Default: "Manually Edit Table"

Number of inputs — Number of model inputs

3 (default) | positive scalar

Specify the number of inputs in the model.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Input method to Manually edit table.

Programmatic Use

Block Parameter: NumSystemInputs

Type: string

Values: positive scalar in quotes

Default: "3"

Workspace — Workspace to import operating point data

Base workspace (default) | Model workspace | Data dictionary

Specify the workspace from which you want to import the operating point data from. The specified workspace must contain the OperatingPoint object with the same name as the value in Operating point variable.

• Base workspace — Import data from base MATLAB^® workspace.

• Model workspace — Import data from the current model workspace.

• Data dictionary — Import data from a Simulink^® data dictionary.

Additionally, to import the operating point data generated by the block in the snapshot mode, click the Save to Workspace button and specify the name of the operating point structure.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Input method to Automatically fill table.

Programmatic Use

Block Parameter: ImportWorkspace

Type: string

Values: "Data dictionary" | "Base workspace" | "Model workspace"

Default: "Data dictionary"

Data dictionary name — Data dictionary name

myDataDictionary.sldd (default) | string

Specify the name of the data dictionary to read the operating point data from. The OperatingPoint object must be stored in the Other Data section of the dictionary. For more information, see What Is a Data Dictionary?.

Dependencies

To enable this parameter, set these parameters.

• Operating mode to Import operating points

• Input method to Automatically fill table

• Workspace to Data dictionary

Programmatic Use

Block Parameter: DataDictionaryName

Type: string

Default: "myDataDictionary.sldd"

Operating point variable — Name of operating point variable

myOperatingPoint (default) | string

Specify the name of the operating point variable.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Input method to Automatically fill table.

Programmatic Use

Block Parameter: OperatingPointVariable

Type: string

Default: "myOperatingPoint"

Snapshot mode — Operating point snapshot mode

Time-based (default) | Event-based

Specify the snapshot mode to obtain the operating point data.

Dependencies

To enable this parameter, set Operating mode to Snapshot operating points.

Programmatic Use

Block Parameter: SnapshotMode

Type: string

Values: "Time-based" | "Event-based"

Default: "Time-based"

Snapshot times (sec) — Simulation snapshot times

[0 1 2] (default) | scalar | vector

Specify the simulation snapshot times at which to extract the operating point of the model. Use a scalar for a single snapshot or a vector for multiple snapshots.

Dependencies

To enable this parameter, set Operating mode to Snapshot operating points and Snapshot mode to Time-based.

Programmatic Use

Block Parameter: SnapshotTimes

Type: string

Values: scalar or vector in quotes

Default: "[1 2 3]"

Use external source — Use input port for snapshot times

off (default) | on

Specify the simulation snapshot times as block input.

Dependencies

To enable this parameter, set Operating mode to Snapshot operating points and Snapshot mode to Time-based.

Programmatic Use

Block Parameter: SnapshotTimesExternalSource

Type: string

Value "off" | "on"

Default: "off"

Sample time (-1 for inherited) — Sample time

-1 (default) | positive scalar

Specify the sample time.

Dependencies

To enable this parameter, set Operating mode to Snapshot operating points and Snapshot mode to Time-based.

Programmatic Use

Block Parameter: SampleTime

Type: string

Values: positive scalar in quotes | "–1"

Default: "–1"

Operating point definitions — Operating point data

multiple table entries

Operating point data, specified as multiple table entries.

When the Input Method is Manually edit table, use the Value column of the table to manually specify the corresponding data for index, snapshot time, and input level of the operating points.

When the Input Method is Automatically fill table, the Value show the value of the operating point based on the imported operating point.

To populate the entries of the table after obtaining the data in snapshot mode, click Save to Table.

Dependencies

To enable manual data entry for the Value column of this table, set Operating mode to Import operating points and Input method to Manually edit table.

Programmatic Use

Block Parameter: OperatingPointTable

Type: string

Values: cell array in quotes

Default: "{'Indicies','[1 2 3]';'Times (sec)','[0 1 2]';'SystemInput_1','[1 1 1]';'SystemInput_2','[2 2 2]';'SystemInput_3','[3 3 3]'}"

Bus name — Name of bus object

scdPlantOPsBusObject (default) | string

Specify a name for the Simulink.Bus object created by the block.

Programmatic Use

Block Parameter: BusName

Type: string

Values: string

Default: "scdPlantOPsBusObject"

Specify bus name — Specify bus name

off (default) | on

Specify a bus name for the object manually.

Programmatic Use

Block Parameter: SpecifyBusName

Type: string

Value "off" | "on"

Default: "off"

Data Type — Floating point precision

Double (default) | Single

Specify the floating-point precision based on simulation environment or hardware requirements.

Programmatic Use

Block Parameter: BlockDataType

Type: string

Values: "Double" | "Single"

Default: "Double"

Change operating point setting Tab

Use block for autotuning — Use block for PID autotuning workflow

on (default) | off

Use the block for gain-scheduled PID autotuning workflow. When you enable this option, the block generates a signal at the start_stop output port. Use the start_stop signal to start and stop the autotuning process with the Closed-Loop PID Autotuner block. The generated signal depends on the additional parameters such as the autotuning method and steady-state settings.

Dependencies

To enable this parameter, set Operating mode to Import operating points.

Programmatic Use

Block Parameter: UseAutotuning

Type: string

Value "off" | "on"

Default: "on"

Method for starting autotuning — Method for starting autotuning

External time vector (default) | Time after reaching steady-state

Specify the method for starting PID autotuning.

• External time vector — Specify a time vector using the autotuning times input port. The value at each index of this vector is the autotuning start time for the operating point at that index. Use the Autotuning time span (sec) parameter to specify the duration of the experiment.

• Time after reaching steady-state — Start the autotuning when the model output reaches steady state. Use the Settling time upper bounds, Settling time lower bounds, and Settling time interval parameters to defined the criteria for steady state of each operating point.

Dependencies

To enable this parameter, set Operating mode to Import operating points and select Use block for autotuning.

Programmatic Use

Block Parameter: AutotuningTriggerMethod

Type: string

Values: "External time vector" | "Time after reaching steady-state"

Default: "External time vector"

Add enable/disable port for autotuning — Add enable/disable port for autotuning

off (default) | on

Add the enable autotuning input port to the block. Use this port to manually specify a scalar flag to enable (1) or disable (0) the autotuning process.

Dependencies

To enable this parameter, set Operating mode to Import operating points and select Use block for autotuning.

Programmatic Use

Block Parameter: AddEnableDisableAutotuning

Type: string

Value "off" | "on"

Default: "on"

Autotuning time span (sec) — Autotuning experiment duration

10 (default) | positive scalar | vector

Specify the duration of the autotuning experiment. You must let the experiment run long enough for the algorithm to collect sufficient data for a good estimate of the plant frequency responses. Running the experiment for insufficient time may result in inaccurate results. For more information, see the start/stop input port of the Closed-Loop PID Autotuner block.

• To run the autotuning experiment with the same duration for all operating points, specify a positive scalar value.

• To run the experiment for different duration for each operating point, specify a vector of positive values. Each duration value corresponds to the operating point at that index of the vector.

Dependencies

To enable this parameter, set Operating mode to Import operating points and select Use block for autotuning.

Programmatic Use

Block Parameter: AutotuningExperimentLength

Type: string

Values: positive scalar or vector in quotes

Default: "10"

Number of samples to start autotuning after reaching steady-state — Delay to start autotuning

2 (default) | positive scalar

Specify the number of samples for which the block delays starting the autotuning process after the model reaches the steady state.

Dependencies

To enable this parameter, use this configuration.

• Set Operating mode to Import operating points.

• Select Use block for autotuning.

• Set Method for starting autotuning to Time after reaching steady-state.

Programmatic Use

Block Parameter: NumAutotuningDelaySamples

Type: string

Values: positive scalar in quotes

Default: "2"

Transition method — Operating point transition method

Internal time vector (from operating point table) (default) | Time after reaching steady-state | Time after completing autotuning | External trigger

Specify the operating point transition method.

• Internal time vector (from operating point table) — Change operating points based on the values in the time vector of the operating point data.

• Time after reaching steady-state — Change operating points after the model output reaches the steady state condition defined for that operating point.

• Time after completing autotuning — Change operating points after the autotuning time span has passed for that operating point.

• External trigger — Change operating point based on the custom logic specified at the next OP block input port.

Dependencies

To enable this parameter, set Operating mode to Import operating points.

Programmatic Use

Block Parameter: TransitionMethod

Type: string

Values: "Internal time vector (from operating point table)" | "Time after reaching steady-state" | "Time after completing autotuning" | "External trigger"

Default: "Internal time vector (from operating point table)"

Change operating point algorithm — Operating point transition algorithm

Step (default) | Ramp

Specify the algorithm to transition from one operating point to another.

• Step — Use a step signal to step between two operating levels.

• Ramp — Use a ramp signal to between two operating levels as a constantly increasing or decreasing signal.

Dependencies

To enable this parameter, set Operating mode to Import operating points.

Programmatic Use

Block Parameter: ChangeOPAlgorithm

Type: string

Value "Step" | "Ramp"

Default: "Step"

Rising slew rate (/sec) — Limit of derivative for increasing input

1 (default) | scalar | vector

Specify the limit of the rising rate of the input signal.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Change operating point algorithm to Ramp.

Programmatic Use

Block Parameter: RampSlewUpRate

Type: string

Values: scalar or vector in quotes

Default: "1"

Falling slew rate (/sec) — Limit of derivative for decreasing input

-1 (default) | scalar | vector

Specify the lower limit on the falling rate of the input signal.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Change operating point algorithm to Ramp.

Programmatic Use

Block Parameter: RampSlewLoRate

Type: string

Values: scalar or vector in quotes

Default: "–1"

Number of samples to transition after reaching steady-state — Delay to transition operating points

2 (default) | nonnegative scalar

Specify the number of samples for which the block delays transition to the next operating point after the model reaches the steady state.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Transition method to Time after reaching steady-state.

Programmatic Use

Block Parameter: NumTransitionDelaySamples

Type: string

Values: nonnegative scalar in quotes

Default: "2"

Number of samples to transition after completing autotuning — Delay to transition operating points

2 (default) | nonnegative scalar

Specify the number of samples for which the block delays transition to the next operating point after the autotuning experiment has completed.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Transition method to Time after completing autotuning.

Programmatic Use

Block Parameter: NumSamplesAutotuningTranstion

Type: string

Values: nonnegative scalar in quotes

Default: "2"

Settling time upper bounds — Upper bound for settling time

[1.1 2.1 3.1] (default) | vector

Specify the upper bound for the operating value used to determine settling time and steady state of the operating point.

Each value of this vector corresponds to the upper bound for the operating point value at that index.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Transition method to Time after reaching steady-state.

Programmatic Use

Block Parameter: SettlingTimeUpper

Type: string

Values: scalar or vector in quotes

Default: "[1.1 2.1 3.1]"

Settling time lower bounds — Lower bound for settling time

[0.9 1.9 2.9] (default) | vector

Specify the lower bound for the operating value used to determine settling time and steady state of the operating point.

Each value of this vector corresponds to the lower bound for the operating point value at that index.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Transition method to Time after reaching steady-state.

Programmatic Use

Block Parameter: SettlingTimeLower

Type: string

Values: scalar or vector in quotes

Default: "[0.9 1.9 2.9]"

Settling time interval — Settling time interval

5 (default) | scalar | vector

Specify the time interval for which the operating condition remains in steady state.

Use a vector to specify different time intervals for different operating points.

Dependencies

To enable this parameter, set Operating mode to Import operating points and Transition method to Time after reaching steady-state.

Programmatic Use

Block Parameter: SettlingTimeInterval

Type: string

Values:scalar or vector in quotes

Default: "5"

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using Simulink® Coder™.

The Change Operating Points block supports code generation only when Operating mode is Import operating points.

Version History

Introduced in R2023b