δx(t) =x(t)−x 0
δu(t) =u(t)−u 0
δy(t) =y(t)−y 0
The linearized model in terms of δx, δu, and δy is valid when the values of these variables
are small:
δx ̇(t) =Aδx(t)+Bδu(t)
δy(t) =Cδx(t)+Dδu(t)
Applications of Linearization
Linearization is useful in model analysis and control design applications.
Exact linearization of the specified nonlinear Simulink model produces linear state-space,
transfer-function, or zero-pole-gain equations that you can use to:
- Plot the Bode response of the Simulink model.
- Evaluate loop stability margins by computing open-loop response.
- Analyze and compare plant response near different operating points.
- Design linear controller
Classical control system analysis and design methodologies require linear, time-
invariant models. Simulink Control Design automatically linearizes the plant when you
tune your compensator. See “Choose a Control Design Approach” on page 9-2.
- Analyze closed-loop stability.
- Measure the size of resonances in frequency response by computing closed-loop linear
model for control system. - Generate controllers with reduced sensitivity to parameter variations and modeling
errors.
Linearization in Simulink Control Design
You can use Simulink Control Design software to linearize continuous-time, discrete-time,
or multirate Simulink models. The resulting linear time-invariant model is in state-space
form.
Linearize Nonlinear Models