Set options for systune


options = systuneOptions
options = systuneOptions(Name,Value)


options = systuneOptions returns the default option set for the systune command.

options = systuneOptions(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.

systuneOptions takes the following Name arguments:


Amount of information to display during systune runs.

Display takes the following values:

  • 'final' — Display a one-line summary at the end of each optimization run. The display includes the best achieved values for the soft and hard constraints, fSoft and gHard. The display also includes the number of iterations for each run.


    Final: Soft = 1.09, Hard = 0.68927, Iterations = 58
  • 'sub' — Display the result of each optimization subproblem.

    When you use both soft and hard tuning goals, the software solves the optimization as a sequence of subproblems of the form:


    Here, x is the vector of tunable parameters, f(x) is the largest normalized soft-constraint value, and g(x) is the largest normalized hard-constraint value. (See the "Algorithms" section of the systune reference page for more information.) The software adjusts the multiplier α so that the solution of the subproblems converges to the solution of the original constrained optimization problem. When you select 'sub', the report includes the results of each of these subproblems.


    alpha=0.1: Soft = 3.97, Hard = 0.68927, Iterations = 8
    alpha=0.5036: Soft = 1.36, Hard = 0.68927, Iterations = 8
    alpha=1.47: Soft = 1.09, Hard = 0.68927, Iterations = 42
    Final: Soft = 1.09, Hard = 0.68927, Iterations = 58
  • 'iter' — Display optimization progress after each iteration. The display includes the value after each iteration of the objective parameter being minimized. The objective parameter is whichever is larger of αf(x) and g(x). The display also includes a progress value that indicates the percent change in the constraints from the previous iteration.


    Iter 1: Objective = 4.664, Progress = 93%
    Iter 2: Objective = 2.265, Progress = 51.4%
    Iter 3: Objective = 0.7936, Progress = 65%
    Iter 4: Objective = 0.7183, Progress = 9.48%
    Iter 5: Objective = 0.6893, Progress = 4.04%
    Iter 6: Objective = 0.6893, Progress = 0%
    Iter 7: Objective = 0.6893, Progress = 0%
    Iter 8: Objective = 0.6893, Progress = 0%
    alpha=0.1: Soft = 3.97, Hard = 0.68927, Iterations = 8
    Iter 1: Objective = 1.146, Progress = 42.7%
    Iter 2: Objective = 1.01, Progress = 11.9%
    alpha=1.47: Soft = 1.09, Hard = 0.68927, Iterations = 42
    Final: Soft = 1.09, Hard = 0.68927, Iterations = 58
  • 'off' — Run in silent mode, displaying no information during or after the run.

Default: 'final'


Maximum number of iterations in each optimization run, when the run does not converge to within tolerance.

Default: 300


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

If RandomStart = 0, systune 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.

systune 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


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


Target value for soft constraints.

The optimization stops when the largest soft constraint value falls below the specified SoftTarget value. The default value SoftTarget = 0 minimizes the soft constrains subject to satisfying the hard constraints.

Default: 0


Relative tolerance for termination.

The optimization terminates when the relative decrease in the soft constraint value decreases by less than SoftTol over 10 consecutive iterations. Increasing SoftTol speeds up termination, and decreasing SoftTol yields tighter final values.

Default: 0.001


A priori estimate of best soft constraint value.

For problems that mix soft and hard constraints, providing a rough estimate of the optimal value of the soft constraints (subject to the hard constraints) helps to speed up the optimization.

Default: 1


Minimum decay rate for closed-loop poles.

Constrains all closed-loop pole locations |p| to satisfy Re(p) < -MinDecay. Adjust the minimum value if the optimization cannot meet the default minimum value, or if the default minimum value conflicts with other requirements. For specifying other constraints on the closed-loop pole locations, use TuningGoal.Poles.

Default: 1e-7

Output Arguments


Option set containing the specified options for the systune command.


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Create Options Set for systune

Create an options set for a systune run using five random restarts. Also, set the display level to show the progress of each iteration, and increase the relative tolerance of the soft constraint value to 0.01.

options = systuneOptions('RandomStart',5,'Display','iter',...

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

options = systuneOptions;
options.RandomStart = 5;
options.Display = 'iter';
options.SoftTol = 0.01;

Configure Option Set for Parallel Optimization Runs

Configure an option set for a systune 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 systune tuning of fixed-structure control systems. When you run multiple randomized systune 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, manually start a parallel pool using parpool. For example:


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

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

options = systuneOptions('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 systuneOptions set when you call systune. For example, suppose you have already created a tunable control system model, CLO. For tuning this system, you have created vectors SoftReqs and HardReqs of TuningGoal requirements objects. These vectors represent your soft and hard constraints, respectively. In that case, the following command uses parallel computing to tune the control system of CL0.

[CL,fSoft,gHard] = systune(CL0,SoftReqs,HardReqs,options);

Introduced in R2012b

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