Design Of Robust Control Systems

A study of the practical aspects in designing feedback control systems in which the plant may be non-minimum phase, unstable and also highly uncertain. Classical (QFT) and modern (Hoo) design approaches are explained side-by-side and are used to solve design examples.

To a large extent, our lives on this earth depend on systems that operate auto matically. Manysuchsystems can be found in nature and others are man made. These systems can be biological, electrical, mechanical, chemical, or ecological, to namejust a few categories. Our human body is full ofsystems whose conti nued automatic operation is vital for our existence. On a daily basis we come in contact with man made systems whose automatic operation ensures increa sed productivity, promotes economic development and improves the quality of life. A primary component that is responsible for the automatic operation of a system is a device or mechanism called the controller. In man made systems one must first design and then implement such a controller either as a piece of hardware or as software code in a computer. The safe and efficient automatic operation of such systems is testimony to the success of control theorists and practitioners over the years. This book presents new methods {or controller design. The process ofdeveloping a controller or control strategy can be dramatically improved if one can generate an appropriate dynamic model for the system under consideration. Robust control design deals with the question of how to develop such controllers for system models with uncertainty. In many cases dynamic models can be expressed in terms oflinear, time invariant differential equations or transfer functions.

Self-contained introduction to control theory that emphasizes on the most modern designs for high performance and robustness. It assumes no previous coursework and offers three chapters of key topics summarizing classical control. To provide readers with a deeper understanding of robust control theory than would be otherwise possible, the text incorporates mathematical derivations and proofs. Includes many elementary examples and advanced case studies using MATLAB Toolboxes.

This is a unified collection of important recent results for the design of robust controllers for uncertain systems, primarily based on H8 control theory or its stochastic counterpart, risk sensitive control theory. Two practical applications are used to illustrate the methods throughout.

Shows readers how to exploit the capabilities of the MATLAB® Robust Control and Control Systems Toolboxes to the fullest using practical robust control examples.

This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework. Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering. Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches. Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.

The aim of this book is to present the theoretical and practical aspects of embedded robust control design and implementation with the aid of MATLAB(R) and SIMULINK(R). It covers methods suitable for practical implementations, combining knowledge from control system design and computer engineering to describe the entire design cycle.

Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements. Providing a range of solutions to control and signal processing problems, this book: * Presents a comprehensive introduction to the polynomial systems approach for the solution of H_2 and H_infinity optimal control problems. * Develops robust control design procedures using frequency domain methods. * Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems. * Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement. * Considers time-varying control and signal processing problems. * Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions. Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.