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2000 | Buch

A Course in Robust Control Theory

A Convex Approach

verfasst von: Geir E. Dullerud, Fernando Paganini

Verlag: Springer New York

Buchreihe : Texts in Applied Mathematics

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Über dieses Buch

Research in robust control theory has been one of the most active areas of mainstream systems theory since the late 70s. This research activity has been at the confluence of dynamical systems theory, functional analysis, matrix analysis, numerical methods, complexity theory, and engineering applications. The discipline has involved interactions between diverse research groups including pure mathematicians, applied mathematicians, computer scientists and engineers. This research effort has produced a rather extensive set of approaches using a wide variety of mathematical techniques, and applications of robust control theory are spreading to areas as diverse as control of fluids, power networks, and the investigation of feddback mechanisms in biology. During the 90's the theory has seen major advances and achieved a new maturity, centered around the notion of convexity. The goal of this book is to give a graduate-level course on robust control theory that emphasizes these new developments, but at the same time conveys the main principles and ubiquitous tools at the heart of the subject. Its pedagogical objectives are to introduce a coherent and unified framework for studying robust control theory, to provide students with the control-theoretic background required to read and contribute to the research literature, and to present the main ideas and demonstrations of the major results of robust control theory. The book will be of value to mathematical researchers and computer scientists wishing to learn about robust control theory, graduate students planning to do research in the area, and engineering practitioners requiring advanced control techniques.

Inhaltsverzeichnis

Frontmatter
0. Introduction
Abstract
In this course we will explore and study a mathematical approach aimed directly at dealing with complex physical systems that are coupled in feedback. The general methodology we study has analytical applications to both human-engineered systems and systems that arise in nature, and the context of our course will be its use for feedback control.
Geir E. Dullerud, Fernando Paganini
1. Preliminaries in Finite Dimensional Space
Abstract
This chapter is centered around finite dimension vector spaces, mappings on them, and the convexity property.
Geir E. Dullerud, Fernando Paganini
2. State Space System Theory
Abstract
We will now begin our study of system theory. This chapter is devoted to examining one of the building blocks used in the foundation of this course, the continuous time, state space system. Our goal is to cover the fundamentals of state space systems, and we will consider and answer questions about their basic structure, controlling and observing them, and representations of them.
Geir E. Dullerud, Fernando Paganini
3. Linear Analysis
Abstract
One of the prevailing viewpoints for the study of systems and signals is that in which a dynamical system is viewed as a mapping between input and output functions. This concept underlies most of the basic treatments of signal processing, communications, and control. Although a functional analytic perspective is implicit in this viewpoint, the associated machinery is not commonly applied to the study of dynamical systems. In this course we will see that incorporating more tools from analysis (e.g., function spaces, operators) into this conceptual picture leads to methods of key importance for the study of systems. In particular, operator norms provide a natural way to quantify the “size” of a system, a fundamental requirement for a quantitative theory of system uncertainty and model approximation.
Geir E. Dullerud, Fernando Paganini
4. Model Realizations and Reduction
Abstract
In this chapter we start our investigation of quantitative input and output properties of systems. To do this we will require the state space systems theory of Chapter 2 combined with the new viewpoint and framework gained in the preceding chapter. We first consider issues related to the relative controllability and observability of system states, and their relationships with the overall input-output characteristics of a system. We then turn to the important question of systematically finding reduced order approximations to systems. We will develop a powerful technique to accomplish this, and the operator perspective of the previous chapter will play a central role.
Geir E. Dullerud, Fernando Paganini
5. Stabilizing Controllers
Abstract
We begin here our study of feedback design, which will occupy our attention in the next three chapters. In these chapters we will consider systematic design methods where objectives are first specified, and one can then exactly characterize when the specifications can be met, as well as find suitable controllers. In other words, design is based solely on clearly formulated specifications, rather than on a specific strategy chosen a priori.
Geir E. Dullerud, Fernando Paganini
6. H 2 Optimal Control
Abstract
In this chapter we begin our study of optimal synthesis and in particular will derive controllers that optimize the H 2 performance criterion. We will start by defining the synthesis problem to be solved, and will then provide a number of motivating interpretations. Following this, we will develop some new matrix tools for the task at hand, before proceeding to solve this optimal control problem.
Geir E. Dullerud, Fernando Paganini
7. H ∞ Synthesis
Abstract
In this chapter we consider optimal synthesis with respect to the H norm introduced in Chapter 3. Again we are concerned with the feedback arrangement of Figure 6.1 where we have two state space systems G and K, each having their familiar role.
Geir E. Dullerud, Fernando Paganini
8. Uncertain Systems
Abstract
In the last three chapters we have developed synthesis techniques for feedback systems where the plant model was completely specified, in the sense that given any input there is a uniquely determined output. Also our plant models were linear, time invariant, and finite dimensional. We now return our focus to analysis, but move beyond our previous restriction of having complete system knowledge to the consideration of uncertain systems.
Geir E. Dullerud, Fernando Paganini
9. Feedback Control of Uncertain Systems
Abstract
In this chapter we bring together the separate threads of synthesis of feedback controllers in the absence of uncertainty, and analysis of uncertain systems, into a common problem involving both uncertainty and control. This problem is represented by the diagram shown in Figure 9.1, where G is the generalized plant as in earlier chapters, but now also describes dependence on system uncertainty. The perturbation Δ belongs to a structured ball, and K represents the controller.
Geir E. Dullerud, Fernando Paganini
10. Further Topics: Analysis
Abstract
At this point we have achieved the major goals of our course — the detailed study of the topics in Chapters 1 through 9. This chapter and the next are devoted to broadening and deepening our background by considering a number of additional topics. Our approach will be that of a technical overview, stressing the main ideas and technical machinery, with a somewhat reduced emphasis on formal demonstrations.
Geir E. Dullerud, Fernando Paganini
11. Further Topics: Synthesis
Abstract
We have arrived at the final chapter of this course. As with the preceding chapter our main objective is to acquire some familiarity with two new topics, and again our treatment will be of a survey nature. The areas we will consider are linear parameter varying systems, multidimensional systems, and linear time-varying (LTV) systems. In Chapter 10 we covered new analysis techniques and problems, and our aim in this chapter is the study of additional methods and results pertaining to synthesis.
Geir E. Dullerud, Fernando Paganini
Backmatter
Metadaten
Titel
A Course in Robust Control Theory
verfasst von
Geir E. Dullerud
Fernando Paganini
Copyright-Jahr
2000
Verlag
Springer New York
Electronic ISBN
978-1-4757-3290-0
Print ISBN
978-1-4419-3189-4
DOI
https://doi.org/10.1007/978-1-4757-3290-0