Model and Controller Simplification
Complex models are not always required for good control. Optimization methods, including methods based on H∞, H2, and µ-synthesis optimal control theory, generally produce controllers with at least as many states as the plant model. Model-order reduction commands help you to find less complex low-order approximations to plant and controller models.
|Model reduction from normalized coprime factorization|
|Simplified access to Hankel singular value based model reduction functions|
|Balanced model truncation via square root method|
|Hankel minimum degree approximation (MDA) without balancing|
|Compute Hankel singular values for stable/unstable or continuous/discrete system|
|Modal form realization and projection|
|Balanced model truncation via Schur method|
|Reduced order model|
|Slow and fast modes decomposition|
- Why Reduce Model Order?
In the design of robust controllers for complicated systems, model reduction fits several goals.
- Hankel Singular Values
Hankel singular values define the energy of each state in the system. Model reduction techniques based on Hankel singular values can achieve a reduced-order model that preserves important system characteristics.
- Model Reduction Techniques
Model reduction routines are categorized into two groups, additive error and multiplicative error types.
- Approximate Plant Model by Additive Error Methods
Reduce a model with
balancmrand examine the resulting model error.
- Approximate Plant Model by Multiplicative Error Method
Reduce a model with
bstmrand examine the resulting model error.
- Using Modal Algorithms
modreallets you reduce a model while preserving jω-axis poles.
- Reducing Large-Scale Models
modrealcan be the best way to start when reducing large models.
- Normalized Coprime Factor Reduction
Compute a reduced-order model by truncating a balanced coprime set of a model.
- Simplifying Representation of Uncertain Objects
Simplify uncertain models built up from uncertain elements to ensure that the internal representation of the model is minimal.