Learn more about Simulink Control Design

Purpose of Linearization

Many common control system analysis and design methodologies require linear, time-invariant models. However, control systems and physical models created with Simulink are often nonlinear and time-varying. Linearization is the approximation of a nonlinear system as a linear system, based on the assumption that the system is almost linear within a certain range of operation. With a linearized model you can

• Use the Control System Toolbox LTI Viewer to display and analyze the dynamic behaviors of a model.

• Use the compensator design tools in the Control System Toolbox software, the Robust Control Toolbox™ software, and the Model Predictive Control Toolbox™ software to tune control systems.

• Express a model as a transfer function, state space model, or zero-pole-gain model.

• Determine the response of a model to arbitrary input signals.

A linearized model can provide a good approximation to a nonlinear system when created and used carefully. Factors affecting the accuracy of the approximation are

• Choice of operating points. See Why Are Operating Points Important?.

• Understanding the equations for the linearized model. See What Is Linearization?.

• Controlling the effect of feedback loops. See What Is Open-Loop Analysis?.

Introduction

Role of Linearization in Compensator Design

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