Robust Control Toolbox™ commands let you apply the powerful methods of
H∞ synthesis to
control design problems. You can use
tune fixed-structure control systems, which are control systems that
have predefined architectures and controller structures. Commands such
hinfsyn perform traditional synthesis of
full-order, centralized controllers. For more information about the
difference, see Difference Between Fixed-Structure Tuning and Traditional H-Infinity Synthesis.
|H∞ tuning of fixed-structure controllers|
|Set options for hinfstruct|
|Compute H-infinity optimal controller|
|Option set for |
|Full-control H-infinity synthesis|
|Full-information H-infinity synthesis|
|Compute H2 optimal controller|
|Option set for |
|Compute H∞ controller for sampled-data system|
|Mixed H2/H∞ synthesis with regional pole placement constraints|
|H∞ norm of dynamic system|
|Weighting function with monotonic gain profile|
|Generate Bessel, Butterworth, Chebyshev, or RC filter|
|Plant augmentation for weighted mixed-sensitivity H∞ and H2 loop-shaping design|
Fixed-structure control systems are have predefined architectures and controller structures.
Traditional H∞ synthesis designs a full-order, centralized controller. Fixed-structure tuning lets you specify your control architecture and the structure and parameterization of the tunable elements of your system.
hinfstruct lets you use H∞ synthesis
to tune control systems that have predefined architectures and controller
hinfstruct, you express
your design requirements as constraints on the closed-loop gain.
Get an overview of the steps required to perform structured H∞ synthesis.
This example shows the complete workflow for tuning
a control system with
To tune a control system with
create a generalized LTI model of the system that includes the fixed
and tunable elements and weighting functions that represent your design
hinfstruct to tune the tunable
parameters in the
genss model of your control
hinfstruct returns a tuned version
of the control system model a parameter that indicates how well the
requirements are met.
To validate the
design, examine the performance of the tuned system.
If you have the Parallel Computing Toolbox™ software installed, you can speed up the tuning of fixed-structure control systems.
In this example, use H∞ synthesis to design a controller for a nominal plant model. Then, use μ synthesis to design a robust controller that accounts for uncertainty in the model.
This example shows how to use Robust Control Toolbox™ to design a robust controller (using D-K iteration) and to do robustness analysis on a process control problem.
For MIMO systems the transfer functions are matrices, and relevant measures of gain are determined by singular values, H∞, and H2 norms.
There are several ways of defining norms of a scalar signal, which have different physical interpretations and provide different measures of performance.
Many types of control objectives can be posed as a minimization of norms of closed-loop transfer functions.