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1997 | Buch

Fundamental Limitations in Filtering and Control

verfasst von: María M. Seron, PhD, Julio H. Braslavsky, PhD, Graham C. Goodwin

Verlag: Springer London

Buchreihe : Communications and Control Engineering

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Über dieses Buch

This book deals with the issue of fundamental limitations in filtering and control system design. This issue lies at the very heart of feedback theory since it reveals what is achievable, and conversely what is not achievable, in feedback systems. The subject has a rich history beginning with the seminal work of Bode during the 1940's and as subsequently published in his well-known book Feedback Amplifier Design (Van Nostrand, 1945). An interesting fact is that, although Bode's book is now fifty years old, it is still extensively quoted. This is supported by a science citation count which remains comparable with the best contemporary texts on control theory. Interpretations of Bode's results in the context of control system design were provided by Horowitz in the 1960's. For example, it has been shown that, for single-input single-output stable open-loop systems having rela­ tive degree greater than one, the integral of the logarithmic sensitivity with respect to frequency is zero. This result implies, among other things, that a reduction in sensitivity in one frequency band is necessarily accompa­ nied by an increase of sensitivity in other frequency bands. Although the original results were restricted to open-loop stable systems, they have been subsequently extended to open-loop unstable systems and systems having nonminimum phase zeros.

Inhaltsverzeichnis

Frontmatter

Introduction

Frontmatter
1. A Chronicle of System Design Limitations
Abstract
This book is concerned with fundamental limits in the design of feedback control systems and filters. These limits tell us what is feasible and, conversely, what is infeasible, in a given set of circumstances. Their significance arises from the fact that they subsume any particular solution to a problem by defining the characteristics of all possible solutions.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin

Limitations in Linear Control

Frontmatter
2. Review of General Concepts
Abstract
This chapter collects some concepts related to linear, time-invariant systems, as well as properties of feedback control systems. It is mainly intended to introduce notation and terminology, and also to provide motivation and a brief review of the background material for Part II. The interested reader may find a more extensive treatment of the topics covered here in the books and papers cited in the Notes and References section at the end of the chapter.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
3. SISO Control
Abstract
In this chapter we present results on performance limitations in linear single-input single-output control systems. These results are the cornerstones of classical design. We focus on the sensitivity and complementary sensitivity functions, S and T. Although this chapter is based on contributions by many authors, mainly during the 80’s, they may be seen with justice as direct descendants of the many ideas contained in Bode (1945).
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
4. MIMO Control
Abstract
This chapter investigates sensitivity limitations in multivariable linear control. There are different ways of extending the scalar results to a multivariable setting. We follow here two approaches, namely, one that considers integral constraints on the singular values of the sensitivity functions, and a second that develops integral constraints on sensitivity vectors. These approaches complement each other, in the sense that they find application in different problems, and hence both are needed to obtain a general view of multivariable design limitations imposed by ORHP zeros and poles. In order to avoid repetition, we use the first approach to derive the multivariable version of Bode’s integral theorems, whilst the second approach is taken to obtain the multivariable extension of the Poisson integrals. Both approaches emphasize the multivariable aspects of the problem by taking into account, in addition to location, the directions of zeros and poles.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
5. Extensions to Periodic Systems
Abstract
Periodic dynamical systems frequently arise in applications. Examples include batch processes that are taken through a periodic operating cycle, and systems where periodic or multirate sampling strategies are employed (Feuer & Goodwin 1996). A periodic system is time-varying in nature; however, by using time or frequency domain raising techniques, it is possible to reduce the analysis to that of a special LTI multivariable system.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
6. Extensions to Sampled-Data Systems
Abstract
This chapter deals with fundamental limitations for sampled-data (SD) feedback systems. By the term SD, we refer to a system with both continuous-time and discrete-time signals — as is the case of digital control of an analogue plant — but which is studied in continuous-time. This contrasts with the approach taken in §3.4 in Chapter 3, where we were concerned only with the sampled behavior of the system. In this chapter, the full intersample behavior will be taken into account.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin

Limitations in Linear Filtering

Frontmatter
7. General Concepts
Abstract
This chapter sets up the general framework for the discussion in Part III regarding sensitivity limitations in filter design. In particular, two main concepts are introduced here: filtering sensitivity functions and bounded error estimators. These concepts are the starting point of a theory of design limitations for a broad class of linear filtering problems, as we will see in the following chapters.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
8. SISO Filtering
Abstract
In this chapter we examine the fundamental design trade-offs that apply to linear scalar filtering problems based on bounded error estimators. We will see that, due to the condition of bounded error estimation, the filtering sensitivity functions introduced in the last chapter are necessarily constrained at points in the complex plane determined by ORHP poles and zeros of the plant. These interpolation constraints, in turn, translate into Poisson and Bode-type integral relations, which show essential limitations in the achievable performance, and induce clear trade-offs in filter design.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
9. MIMO Filtering
Abstract
This chapter investigates sensitivity limitations in multivariable linear filtering. Similar to those obtained in Chapter 4 for the control problem, multivariable integral constraints hold for the MIMO version of the filtering sensitivities introduced in Chapter 7. Also similar to the control case, there are different ways to extend the SISO integrals to a MIMO setting. The approach followed in this chapter emphasizes the trade-offs that arise when the system is required to satisfy, besides frequency conditions, structural specifications on the multivariable sensitivities.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
10. Extensions to SISO Prediction
Abstract
In Chapter 7 we defined filtering sensitivities, P and M, and showed that they satisfy a complementarity constraint. Furthermore, for the class of BEEs, we derived, in Chapters 8 and 9, interpolation and integral constraints that these sensitivities must satisfy. As seen, these constraints quantify fundamental limits on the filter achievable performance.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
11. Extensions to SISO Smoothing
Abstract
Following similar developments to those in the previous chapter, a theory of design limitations can also be extended to problems of fixed-lag smoothing. In this chapter, we define appropriate complementary sensitivities and obtain fundamental limitations that apply to scalar smoothers derived from BEEs.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin

Limitations in Nonlinear Control and Filtering

Frontmatter
12. Nonlinear Operators
Abstract
In Chapters 13 and 14 we will investigate fundamental constraints that hold for the problems of nonlinear feedback control and nonlinear filtering. The general framework used is that of input-output nonlinear operators acting on linear signal spaces. Within this framework, the linear concepts of nonminimum phase zeros and unstable poles of transfer functions are easily handled using ideas of defect in the domain and range of the nonlinear operators. Some properties of this approach essential to our analysis are reviewed in this chapter.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
13. Nonlinear Control
Abstract
This chapter analyzes performance limitations and stability robustness of the unity feedback configuration of Figure 12.2 considered in Chapter 12. We use the material on nonlinear operator theory developed in §12.1.1 of Chapter 12.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
14. Nonlinear Filtering
Abstract
This chapter represents a preliminary extension to the nonlinear case of the sensitivity approach to filtering of Chapters 8 and 9. We use the background on nonlinear operators given in Chapter 12. Indeed, we first study the complementarity of the filtering sensitivities in the framework of §12.1 and then use the concept of nonlinear cancelations developed in §12.2 to address the issue of stability of the estimation error.
María M. Seron, Julio H. Braslavsky, Graham C. Goodwin
Backmatter
Metadaten
Titel
Fundamental Limitations in Filtering and Control
verfasst von
María M. Seron, PhD
Julio H. Braslavsky, PhD
Graham C. Goodwin
Copyright-Jahr
1997
Verlag
Springer London
Electronic ISBN
978-1-4471-0965-5
Print ISBN
978-1-4471-1244-0
DOI
https://doi.org/10.1007/978-1-4471-0965-5