Skip to Main Content Skip to Search
Accelerating the pace of engineering and science

 

Robust Control Toolbox

Product Description

Reducing Plant and Controller Order

Detailed first-principles or finite-element plant models often have a large number of states. Similarly, H-infinity or mu-synthesis algorithms tend to produce high-order controllers with superfluous states. Robust Control Toolbox provides algorithms that let you reduce the order (number of states) of a plant or controller model while preserving its essential dynamics. As you extract lower-order models, which are more cost effective to implement, you can control the approximation error.

Bode plots comparing magnitude and phase of the original and reduced-order models for the rigid body motion dynamics of a multistory building.

Bode plots comparing magnitude and phase of the original and reduced-order models for the rigid body motion dynamics of a multistory building.

The model reduction algorithms are based on Hankel singular values of the system, which measure the energy of the states. By retaining high-energy states and ignoring low-energy states, the reduced model preserves the essential features of the original model. You can use the absolute or relative approximation error to select the order, and use frequency-dependent weights to focus the model reduction algorithms on specific frequency ranges.

Video: Simplifying Higher-Order Plant Models

Simplifying Higher-Order Plant Models
Approximate high-order plant models with simpler, lower-order models.

Free Control Systems Interactive Kit

Learn more about resources for designing, testing, and implementing control systems.

Get free kit

Trials Available

Try the latest control systems products.

Get trial software
Contact sales
Free technical kit
Trial software

Get Pricing and
Licensing Options