options = hinfstructOptions returns
the default option set for the hinfstruct command.

options = hinfstructOptions(Name,Value) creates
an option set with the options specified by one or more Name,Value pair
arguments.

Input Arguments

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments.
Name is the argument
name and Value is the corresponding
value. Name must appear
inside single quotes (' ').
You can specify several name and value pair
arguments in any order as Name1,Value1,...,NameN,ValueN.

hinfstructOptions takes the following Name arguments:

'Display'

String determining the amount of information to display during hinfstruct optimization
runs.

Display takes the following values:

'off' — hinfstruct runs
in silent mode, displaying no information during or after the run.

'iter' — display optimization
progress after each iteration. The display includes the value of the
closed-loop H_{∞} norm
after each iteration. The display also includes a Progress value
indicating the percent change in the H_{∞} norm
from the previous iteration.

'final' — display a one-line
summary at the end of each optimization run. The display includes
the minimized value of the closed-loop H_{∞} norm
and the number of iterations for each run.

Default: 'final'

'MaxIter'

Maximum number of iterations in each optimization run.

Default: 300

'RandomStart'

Number of additional optimizations starting from random values
of the free parameters in the controller.

If RandomStart = 0, hinfstruct performs
a single optimization run starting from the initial values of the
tunable parameters. Setting RandomStart = N > 0 runs N additional
optimizations starting from N randomly generated
parameter values.

hinfstruct finds a local minimum of the
gain minimization problem. To increase the likelihood of finding parameter
values that meet your design requirements, set RandomStart > 0. You can then use the
best design that results from the multiple optimization runs.

Use with UseParallel = true to distribute
independent optimization runs among MATLAB^{®} workers (requires Parallel Computing Toolbox™ software).

Default: 0

'UseParallel'

Parallel processing flag.

Set to true to enable parallel processing
by distributing randomized starts among workers in a parallel pool.
If there is an available parallel pool, then the software performs
independent optimization runs concurrently among workers in that pool.
If no parallel pool is available, one of the following occurs:

If Automatically create a parallel pool is
selected in your Parallel Computing Toolbox preferences,
then the software starts a parallel pool using the settings in those
preferences.

If Automatically create a parallel pool is
not selected in your preferences, then the software performs the optimization
runs successively, without parallel processing.

If Automatically create a parallel pool is
not selected in your preferences, you can manually start a parallel
pool using parpool before
running the tuning command.

Using parallel processing requires Parallel Computing Toolbox software.

Default: false

'TargetGain'

Target H_{∞} norm.

The hinfstruct optimization stops when
the H_{∞} norm (peak
closed-loop gain) falls below the specified TargetGain value.

Set TargetGain = 0 to
optimize controller performance by minimizing the peak closed-loop
gain. Set TargetGain = Inf to
just stabilize the closed-loop system.

Default: 0

'TolGain'

Relative tolerance for termination. The optimization terminates
when the H_{∞} norm
decreases by less than TolGain over 10 consecutive
iterations. Increasing TolGain speeds up termination,
and decreasing TolGain yields tighter final values.

Default: 0.001

'MaxFrequency'

Maximum closed-loop natural frequency.

Setting MaxFrequency constrains the closed-loop
poles to satisfy |p| <
MaxFrequency.

To let hinfstruct choose the closed-loop
poles automatically based upon the system's open-loop dynamics, set MaxFrequency = Inf. To prevent unwanted
fast dynamics or high-gain control, set MaxFrequency to
a finite value.

Specify MaxFrequency in units of 1/TimeUnit,
relative to the TimeUnit property of the system
you are tuning.

Default: Inf

'MinDecay'

Minimum decay rate for closed-loop poles

Constrains the closed-loop poles to satisfy Re(p) < -MinDecay. Increase this
value to improve the stability of closed-loop poles that do not affect
the closed-loop gain due to pole/zero cancellations.

Specify MinDecay in units of 1/TimeUnit,
relative to the TimeUnit property of the system
you are tuning.

Default: 1e-7

Output Arguments

options

Option set containing the specified options for the hinfstruct command.

Create an options set for a hinfstruct run
using three random restarts and a stability offset of 0.001. Also,
configure the hinfstruct run to stop as soon
as the closed-loop gain is smaller than 1.

Configure an option set for a hinfstruct run
using 20 random restarts. Execute these independent optimization runs
concurrently on multiple workers in a parallel pool.

If you have the Parallel Computing Toolbox software installed,
you can use parallel computing to speed up hinfstruct tuning
of fixed-structure control systems. When you run multiple randomized hinfstruct optimization
starts, parallel computing speeds up tuning by distributing the optimization
runs among workers.

Setting UseParallel to true enables
parallel processing by distributing the randomized starts among available
workers in the parallel pool.

Use the hinfstructOptions set when
you call hinfstruct. For example, suppose you have
already created a tunable closed loop model CL0.
In this case, the following command uses parallel computing to tune CL0.