looptuneOptions

Set options for looptune

Syntax

options = looptuneOptions options = looptuneOptions(Name,Value)

Description

options = looptuneOptions returns the default option set for the looptune command.

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

Input Arguments

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

looptuneOptions takes the following Name arguments:

`GainMargin`	Target gain margin in decibels. `GainMargin` specifies the required gain margin for the tuned control system. For MIMO control systems, the gain margin is the multiloop disk margin. See Stability Analysis Using Disk Margins (Robust Control Toolbox) for the definition of the multiloop disk margin. Default: 7.6 dB
`PhaseMargin`	Target phase margin in degrees. `PhaseMargin` specifies the required phase margin for the tuned control system. For MIMO control systems, the phase margin is the multiloop disk margin. See Stability Analysis Using Disk Margins (Robust Control Toolbox) for the definition of the multiloop disk margin. Default: 45 degrees
`Display`	Amount of information to display during `looptune` runs, specified as one of the following values. `'off'` — Run 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 objective parameter `gam` after each iteration. The display also includes a `Progress` value, indicating the percent change in `gam` from the previous iteration. `'final'` — Display a one-line summary at the end of each optimization run. The display includes the minimized value of `gam` 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`, `looptune` 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. `looptune` tunes by finding a local minimum of a 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. When you use the `RandomStart` option to run multiple randomized optimization starts, you can also use parallel computing to speed up tuning by distributing the optimization runs among workers in a parallel pool. Set this flag to `true` to enable parallel processing. 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 (Parallel Computing Toolbox), 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` (Parallel Computing Toolbox) before running the tuning command. Using parallel processing requires Parallel Computing Toolbox software. Default: `false`
`TargetGain`	Target value for the objective parameter `gam`. The `looptune` command converts your design requirements into normalized gain constraints. The command then tunes the free parameters of the control system to drive the objective parameter `gam` below 1 to enforce all requirements. The default `TargetGain = 1` ensures that the optimization stops as soon as `gam` falls below 1. Set `TargetGain` to a smaller or larger value to continue the optimization or start sooner, respectively. Default: 1
`TolGain`	Relative tolerance for termination. The optimization terminates when the objective parameter `gam` 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 allow `looptune` to 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 looptune command.

Examples

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Create Options Set for looptune

Open Live Script

Create an options set for a looptune run using three random restarts. Also, set the target gain and phase margins to 6 dB and 50 degrees, respectively, and limit the closed-loop pole magnitude to 100.

options = looptuneOptions('RandomStart',3','GainMargin',6,...
                'PhaseMargin',50,'SpecRadius',100);

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

options = looptuneOptions;
options.RandomStart = 3;
options.GainMargin = 6;
options.PhaseMargin = 50;
options.SpecRadius = 100;

Configure Option Set for Parallel Optimization Runs

Configure an option set for a looptune 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 looptune tuning of fixed-structure control systems. When you run multiple randomized looptune optimization starts, parallel computing speeds up tuning by distributing the optimization runs among workers.

If Automatically create a parallel pool is not selected in your Parallel Computing Toolbox preferences (Parallel Computing Toolbox), manually start a parallel pool using parpool (Parallel Computing Toolbox). For example:

parpool;

If Automatically create a parallel pool is selected in your preferences, you do not need to manually start a pool.

Create a looptuneOptions set that specifies 20 random restarts to run in parallel.

options = looptuneOptions('RandomStart',20,'UseParallel',true);

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

Use the looptuneOptions set when you call looptune. For example, suppose you have already created a plant model G0 and tunable controller C0. In this case, the following command uses parallel computing to tune the control system of G0 and C0 to the target crossoverwc.

[G,C,gamma] = looptune(G0,C0,wc,options);

Version History

Introduced in R2016a

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R2016a: Functionality moved from Robust Control Toolbox

Prior to R2016a, this functionality required a Robust Control Toolbox™ license.