Simulink® Control Design™

Product Overview

Introduction

The Simulink^® Control Design™ software provides tools for linearization and compensator design for control systems and models. Linearized models often simplify compensator design and system analysis. This is useful in many industries and applications, including

• Aerospace: flight control, guidance, navigation

• Automotive: cruise control, emissions control, transmission

• Equipment manufacturing: motors, disk drives, servos

The Simulink Control Design software works with the Simulink^® linearization engine and the Control System Toolbox™ SISO Design Tool. Use it to

• Compute operating points of models using specifications or simulation.

• Extract linear models from models.

• Tune compensator blocks in models with either single or multi-loop configurations.

The Simulink Control Design software provides a graphical user interface (GUI) for performing linearization and compensator design for Simulink models. This chapter introduces a Quick Start guide for using this GUI. The remaining chapters give more details on the linearization and compensator design tasks.

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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 addressed in Beginning a Project are

• Choice of operating points. See Specifying Operating Points.

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

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

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Role of Linearization in Compensator Design

Linearized models are especially important for designing compensators. Most compensator design methodologies, such as Bode plots, require a linear plant model. Since most real-world plant models are nonlinear, you must typically linearize the system before you design the compensators for it. As a result, the design of good compensators relies on a good linearization.

The model is automatically linearized for you during compensator design, but it is still important to understand the fundamentals of creating an accurate linear model. Additionally, you should always check that the compensator you designed for the linearized system also works for the nonlinear system. Typically, the compensator works well for the nonlinear system as long as the system does not vary widely from the operating point.

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Introduction

Using the GUI Versus Command-Line Functions