Set options for finding operating points from specifications

returns
an option set with additional options specified by one or more `options`

= findopOptions(`Name,Value`

)`Name,Value`

pair
arguments. Use this option set to specify options for the `findop`

command.

Create an option set for operating point search that sets the optimizer type to gradient descent and suppresses the display output of `findop`

.

option = findopOptions('OptimizerType','graddescent','DisplayReport','off');

Alternatively, use dot notation to set the values of `options`

.

options = findopOptions; options.OptimizerType = 'graddescent'; options.DisplayReport = 'off';

Specify optional
comma-separated pairs of `Name,Value`

arguments. `Name`

is
the argument name and `Value`

is the corresponding value.
`Name`

must appear inside quotes. You can specify several name and value
pair arguments in any order as
`Name1,Value1,...,NameN,ValueN`

.

`'DisplayReport','off'`

suppresses
the display of the operating point search report to the Command Window.`'OptimizerType'`

— Optimizer type used by the optimization algorithm`'graddescent-elim'`

(default) | `'graddescent'`

| `'graddescent-proj'`

| `'lsqnonlin'`

| `'lsqnonlin-proj'`

| `'simplex'`

Optimizer type used by the optimization algorithm, specified
as the comma-separated pair consisting of `'OptimizerType'`

and
one of the following:

`'graddescent-elim'`

— Enforce an equality constraint to force the time derivatives of states to be zero (`dx/dt = 0`

,`x(k+1) = x(k)`

) and output signals to be equal to their specified known values. The optimizer fixes the states,`x`

, and inputs,`u`

, that are marked as`Known`

in an operating point specification, and optimizes the remaining variables.`'graddescent'`

— Enforce an equality constraint to force the time derivatives of states to be zero (`dx/dt = 0`

,`x(k+1) = x(k)`

) and the output signals to be equal to their specified known values. The optimizer also minimizes the error between the states,`x`

, and inputs,`u`

, and their respective known values from an operating point specification. If there are not any inputs or states marked as`Known`

,`findop`

attempts to minimize the deviation between the initial guesses for`x`

and`u`

, and their trimmed values.`'graddescent-proj'`

— In addition to`'graddescent'`

, enforce consistency of model initial conditions at each function evaluation. To specify whether constraints are hard or soft, use the`ConstraintType`

option. This optimization method does not support analytical Jacobians.`'lsqnonlin'`

— Fix the states,`x`

, and inputs,`u`

, marked as`Known`

in an operating point specification, and optimize the remaining variables. The algorithm tries to minimize both the error in the time derivatives of the states (`dx/dt = 0`

,`x(k+1) = x(k)`

) and the error between the outputs and their specified known values.`'lsqnonlin-proj'`

— In addition to`'lsqnonlin'`

, enforce consistency of model initial conditions at each function evaluation. This optimization method does not support analytical Jacobians.`'simplex'`

— Use the same cost function as`lsqnonlin`

with the direct search optimization routine found in`fminsearch`

.

For more information about these optimization algorithms, see `fmincon`

, `lsqnonlin`

,
and `fminsearch`

in the Optimization
Toolbox™ documentation.

`'OptimizationOptions'`

— Options for the optimization algorithmstructure

Options for the optimization algorithm, specified as the comma-separated
pair consisting of `'OptimizationOptions'`

and a
structure created using the `optimset`

function.

`'DisplayReport'`

— Flag indicating whether to display the operating summary report`'on'`

(default) | `'off'`

| `'iter'`

Flag indicating whether to display the operating point summary
report, specified as the comma-separated pair consisting of `'DisplayReport'`

and
one of the following:

`'on'`

— Display the operating point summary report in the MATLAB^{®}command window when running`findop`

.`'off'`

— Suppress display of the summary report.`'iter'`

— Display an iterative update of the optimization progress.

`'AreParamsTunable'`

— Flag indicating whether to recompile the model when varying parameter values`true`

(default) | `false`

Flag indicating whether to recompile the model when varying
parameter values for trimming, specified as the comma-separated pair
consisting of `'AreParamsTunable'`

and one of the
following:

`true`

— Do not recompile the model when all varying parameters are tunable. If any varying parameters are not tunable, recompile the model for each parameter grid point, and issue a warning message.`false`

— Recompile the model for each parameter grid point. Use this option when you vary the values of nontunable parameters.

`'ConstraintType'`

— Constraint types for `'graddescent-proj'`

structure

Constraint types for `'graddescent-proj'`

optimizer
algorithm, specified as the comma-separated pair consisting of
`'ConstraintType'`

and a structure with the
following fields:

`dx`

— Type for constraints on state derivatives`x`

— Type for constraints on state values`y`

— Type for constraints on output values

Specify each constraint as one of the following:

`'hard'`

— Enforce the constraints to be zero.`'soft'`

— Minimize the constraints.

All constraint types are `'hard'`

by default.

`options`

— Trimming options`findopOptions`

option setTrimming options, returned as a `findopOptions`

option
set.

*Behavior changed in R2017b*

The `'graddescent_elim'`

value of the
`Optimizer`

property of a `findopOptions`

object is now `'graddescent-elim'`

.

To update your code, change the optimizer value from
`graddescent_elim`

to
`graddescent-elim`

. The following table shows the typical
usage of this property value and how to update your code.

If your code has this form: | Use this code instead: |
---|---|

opt = findopOptions('Optimizer',... 'graddescent_elim'); |
opt = findopOptions('Optimizer',... 'graddescent-elim') |

opt = findopOptions; opt.Optimizer = 'graddescent_elim'; |
opt = findopOptions; opt.Optimizer = 'graddescent-elim'; |

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