Robustness is often of crucial importance in control system design. Real engineering systems are vulnerable to external disturbance and measurement noise and there are always discrepancies between mathematical models used for design and the actual system in practice.</P>

<EM>Robust Control Design with MATLAB<SUP>®</SUP></EM> helps you learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples ranging from teaching-laboratory experiments, such as a mass&#8211;damper&#8211;spring assembly, to complex systems like a flexible link manipulator are given detailed presentation. All the design exercises are conducted using MATLAB<SUP>®</SUP> Robust Control Toolbox, Control System Toolbox and Simulink<SUP>®</SUP>.</P>

By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major <EM>H</EM>-infinity optimization and related methods allowing you quickly to move on with your own challenges.</P>

Features:</P> <UL> <LI>Hands-on, tutorial presentation giving you the opportunity to repeat the designs presented and easily to modify them for your own programs.<U> </U></LI> <LI>An abundance of examples illustrating the most important steps in robust design. </LI></UL>

On the CD-ROM: <UL> <LI>M-files developed with MATLAB<SUP>®</SUP> help you to understand the essence of robust control system design portrayed in the text-based examples. </LI> <LI>MDL- files for simulation of open- and closed-loop control in Simulink<SUP>®</SUP>. </LI> <LI>Full-color interpretations of all suitable figures for extra clarity. </LI></UL>

<EM>Robust Control Design with MATLAB<SUP>®</SUP></EM> is for graduate students and practising engineers who want to learn how to deal with robust control design problems without spending a lot of time in researching complex theoretical developments.</P>

The demonstrations are current for MATLAB<SUP>®</SUP> version 7.01, Robust Control Toolbox version 3.0, Control System Toolbox version 6.1 and Simulink<SUP>®</SUP> version 6.1.</P>