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.
Robust Control Design with MATLAB® 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–damper–spring assembly, to complex systems like a flexible-link manipulator are given detailed presentation. All the design exercises are conducted using MATLAB® Robust Control Toolbox, Control System Toolbox and Simulink®.
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 H-infinity optimization and related methods allowing you quickly to move on with your own challenges.
Features:
• Hands-on, tutorial presentation giving you the opportunity to repeat the designs presented and easily to modify them for your own programs.
• An abundance of examples illustrating the most important steps in robust design.
Robust Control Design with MATLAB® 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.
The demonstrations are current for MATLAB® version 7.01, Robust Control Toolbox version 3.0, Control System Toolbox version 6.1 and Simulink® version 6.1.
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.
Robust Control Design with MATLAB® 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–damper–spring assembly, to complex systems like a flexible link manipulator are given detailed presentation. All the design exercises are conducted using MATLAB® Robust Control Toolbox, Control System Toolbox and Simulink®.
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 H-infinity optimization and related methods allowing you quickly to move on with your own challenges.
Features:
Robust Control Design with MATLAB® 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.
The demonstrations are current for MATLAB® version 7.01, Robust Control Toolbox version 3.0, Control System Toolbox version 6.1 and Simulink® version 6.1.
Robustness is often of crucial importance in control system design. This book helps readers learn how to use well-developed advanced robust control design methods in practical cases. Several realistic control design examples ranging from teaching-laboratory experiments to complex systems are given detailed presentation. The hands-on, tutorial presentation gives readers the opportunity to repeat the designs presented and modify them for their own programs.
Da-Wei Gu
Control Control Applications Control Engineering Control Systems Design Control Systems Toolbox Control Theory H-infinity Control MATLAB® RSI Robust Control Robust Control Toolbox Simulink® modeling mu-synthesis
From the reviews of the first edition:"The main value of the book is its illustrative character showing how methodologies in robust control are implemented and what is the activity of control designers. So the book is for practitioners." (A. Akutowicz, Zentralblatt MATH, Vol. 1086, 2006)
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