# Uncertain Models

Uncertain state-space (`uss`

) models are linear
systems with uncertain state-space matrices, uncertain linear dynamics,
or both. Most functions that work on numeric LTI models also work on
`uss`

models. These include model interconnection
functions such as `connect`

and
`feedback`

, and linear analysis functions such as
`bode`

and `stepinfo`

. Some
functions that generate plots, such as `bode`

and
`step`

, plot random samples of the uncertain
model to give you a sense of the distribution of uncertain
dynamics.

In addition, you can use functions such as
`robstab`

and `wcgain`

to
perform robustness and worst-case analysis of uncertain systems
represented by `uss`

models. You can also use tuning
functions such as `systune`

for robust controller
tuning.

## Functions

## Topics

### Uncertain Models

**Introduction to Uncertain Elements**

Uncertain elements are the building blocks for representing systems with uncertainty.

**Create Models of Uncertain Systems**

Represent uncertain parameters and unmodeled dynamics in linear time-invariant models.

**Uncertain Model Interconnections**

Interconnect models that include systems with uncertain parameters or dynamics.**Simplifying Representation of Uncertain Objects**

Simplify uncertain models built up from uncertain elements to ensure that the internal representation of the model is minimal.**Decomposing Uncertain Objects**

Access the normalized LFT representation underlying uncertain models.

### Model Object Basics

**What Are Model Objects?**

Model objects represent linear systems as specialized data containers that encapsulate model data and attributes in a structured way.**Types of Model Objects**

Model object types include numeric models, for representing systems with fixed coefficients, and generalized models for systems with tunable or uncertain coefficients.

**Control System Modeling with Model Objects**

Build models that represent your control system using model objects.