Feedback for physicists: A tutorial essay on control
TL;DR: In this paper, a tutorial essay aims to give enough of the formal elements of control theory to satisfy the experimentalist designing or running a typical physics experiment and enough to satisfy a theorist wishing to understand its broader intellectual context.
Abstract: Feedback and control theory are important ideas that should form part of the education of a physicist but rarely do. This tutorial essay aims to give enough of the formal elements of control theory to satisfy the experimentalist designing or running a typical physics experiment and enough to satisfy the theorist wishing to understand its broader intellectual context. The level is generally simple, although more advanced methods are also introduced. Several types of applications are discussed, as the practical uses of feedback extend far beyond the simple regulation problems where it is most often employed. Sketches are then provided of some of the broader implications and applications of control theory, especially in biology, which are topics of active research.
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01 Apr 2003
TL;DR: The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it as mentioned in this paper, and also presents new ideas and alternative interpretations which further explain the success of the EnkF.
Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.
2,975 citations
Book•
21 Apr 2008
TL;DR: Feedback Systems develops transfer functions through the exponential response of a system, and is accessible across a range of disciplines that utilize feedback in physical, biological, information, and economic systems.
Abstract: This book provides an introduction to the mathematics needed to model, analyze, and design feedback systems. It is an ideal textbook for undergraduate and graduate students, and is indispensable for researchers seeking a self-contained reference on control theory. Unlike most books on the subject, Feedback Systems develops transfer functions through the exponential response of a system, and is accessible across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl strm and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. strm and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. They provide exercises at the end of every chapter, and an accompanying electronic solutions manual is available. Feedback Systems is a complete one-volume resource for students and researchers in mathematics, engineering, and the sciences.Covers the mathematics needed to model, analyze, and design feedback systems Serves as an introductory textbook for students and a self-contained resource for researchers Includes exercises at the end of every chapter Features an electronic solutions manual Offers techniques applicable across a range of disciplines
1,927 citations
Cites background from "Feedback for physicists: A tutorial..."
...The book by Fradkov [77] and the tutorial article by Bechhoefer [25] cover many specific topics of interest to the physics community....
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TL;DR: In this article, the basic principles of modern optical magnetometers, discuss fundamental limitations on their performance, and describe recently explored applications for dynamical measurements of biomagnetic fields, detecting signals in NMR and MRI, inertial rotation sensing, magnetic microscopy with cold atoms, and tests of fundamental symmetries of nature.
Abstract: Some of the most sensitive methods of measuring magnetic fields use interactions of resonant light with atomic vapour. Recent developments in this vibrant field have led to improvements in sensitivity and other characteristics of atomic magnetometers, benefiting their traditional applications for measurements of geomagnetic anomalies and magnetic fields in space, and opening many new areas previously accessible only to magnetometers based on superconducting quantum interference devices. We review basic principles of modern optical magnetometers, discuss fundamental limitations on their performance, and describe recently explored applications for dynamical measurements of biomagnetic fields, detecting signals in NMR and MRI, inertial rotation sensing, magnetic microscopy with cold atoms, and tests of fundamental symmetries of nature.
1,489 citations
Cites background from "Feedback for physicists: A tutorial..."
...However, if the bandwidth is increased by a factor K over the natural bandwidth, the magnetometer output noise also increases by the same factor K [47]....
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TL;DR: In this article, B. Sonnenschein, E.R. dos Santos, P.J. Schultz, C.A. Ha, M.K. Choi and C.P.
683 citations
TL;DR: This work addresses the physically important issue of the energy required for achieving control by deriving and validating scaling laws for the lower and upper energy bounds.
Abstract: The outstanding problem of controlling complex networks is relevant to many areas of science and engineering, and has the potential to generate technological breakthroughs as well. We address the physically important issue of the energy required for achieving control by deriving and validating scaling laws for the lower and upper energy bounds. These bounds represent a reasonable estimate of the energy cost associated with control, and provide a step forward from the current research on controllability toward ultimate control of complex networked dynamical systems.
392 citations
References
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Book•
14 Oct 2002TL;DR: This chapter discusses the design and implementation of Hierarchical Fuzzy Control for a Flexible Robotic Link and Genetic Algorithms in Knowledge Enhancement Implementation Issues Simulation Conclusion References.
Abstract: GENETIC ALGORITHMS Introduction to Genetic Algorithms Terms and Definitions Representation Fitness Function Genetic Operators Genetic Algorithms for Optimization Genetic Programming Conclusions References OPTIMAL ROBUST CONTROL Introduction to the Control Theory Norms of Signals and Functions Description of Model Uncertainty Robust Stability and Disturbance Rejection Controller Design Optimization Conclusions References METHODS FOR CONTROLLER DESIGN USING GENETIC ALGORITHMS Introduction to Controller Design Using Genetic Algorithms Design of Optimal Robust Controller with Fixed-Structure Design of Optimal Disturbance Rejection Controller with Fixed Structure Evaluation of the Methods Conclusions References PREDICTIVE AND STRUCTURE VARIABLE CONTROL Model-Based Predictive Controllers Variable Structure Control Systems References DESIGN METHODS, SIMULATION RESULTS, AND CONCLUSIONS Optimization of Generalized Predictive Control Design by Genetic Algorithms Optimization of Quasi-Sliding Mode Control Design by Genetic Algorithms Conclusions References TUNING FUZZY LOGIC CONTROLLERS FOR ROBUST CONTROL SYSTEM DESIGN Introduction Fuzzy Control Genetic Tuning of Fuzzy Control Systems Gas Turbine Engine Control Fuzzy Control System Design - Example Study Applications of GAs for Fuzzy Control References GA-FUZZY HIERARCHICAL CONTROL DESIGN APPROACH Introduction Hierarchical Fuzzy Control for a Flexible Robotic Link Genetic Algorithms in Knowledge Enhancement Implementation Issues Simulation Conclusion References AUTONOMOUS ROBOT NAVIGATION THROUGH FUZZY-GENETIC PROGRAMMING Introduction Hierarchical Fuzzy-Behavior Control Coordination by Behavior Modulation Genetic Programming of Fuzzy Behaviors Evolution of Coordination Autonomous Navigation Results Conclusions Acknowledgements References ROBUST CONTROL SYSTEM DESIGN: A HYBRID H-INFINITY / MULTI-OBJECTIVE OPTIMIZATION APPROACH Introduction H-Infinity Design of Robust Control Systems Multiobjective Optimization Case Study: Robust Control of a Gasification Plant Conclusions APPENDIX: FUZZY SETS, LOGIC AND CONTROL Introduction Classical Sets Classical Set Operations Properties of Classical Sets Fuzzy Sets and Membership Functions Fuzzy Sets Operations Properties of Fuzzy Sets Predicate Logic Fuzzy Logic Fuzzy Control Basic Definitions Conclusion References
75 citations
TL;DR: In this paper, the authors discuss turbulence and image-detection statistics, describe the fundamentals of methods for overcoming turbulence effects, and provide representative performance results for both hardware-and image-processing-based methods.
Abstract: Atmospheric turbulence profoundly limits the angular resolution of astronomical telescopes working at visible and near-infrared wavelengths. In fact, the angular resolution for conventional imaging through turbulence is on the order of 5{endash}20{percent} of the diffraction-limited resolution at the best observatories in the world. The origin of these performance degradations is random turbulence-induced fluctuations in the index of refraction of the atmosphere. Random index-of-refraction fluctuations producing the optical path length of the atmosphere to be random in both space and time, producing random aberrations in the telescope pupil that degrade imaging performance. Over the past several years significant advances have been made in developing both hardware and image-processing-based techniques for improving the resolution of astronomical telescopes. Hardware-oriented correction techniques are based on wave-front sensing and adaptive optics. Image-processing-based methods include speckle-imaging techniques and hybrid imaging techniques that use elements of adaptive-optics systems and image reconstruction. Analysis techniques for predicting the performance of these imaging methods have been developed, and the comparative performance of these imaging techniques has been examined. This paper discusses turbulence and image-detection statistics, describes the fundamentals of methods for overcoming turbulence effects, and provides representative performance results. {copyright} {ital 1997} {ital The American Physical Society}
67 citations
"Feedback for physicists: A tutorial..." refers background in this paper
...Many of these approaches are based on adaptive optics, a technique that has many other applications – for example, compensating for turbulence in astronomy, where one changes rapidly the shape of a mirror to remove phase disturbances added by atmospheric fluctuations (Roggemann et al., 1999)....
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TL;DR: A short history of the discovery of the maximum principle in optimal control theory by L. S. Pontryagin and his associates is presented in this article, where the authors also present a model of optimal control.
Abstract: A short history of the discovery of the maximum principle in optimal control theory by L. S. Pontryagin and his associates is presented.
55 citations
"Feedback for physicists: A tutorial..." refers background or methods in this paper
...The basic insights required to solve such problems with constraints on the control variables came after three consecutive, sleepless nights Gamkrelidze, 1999 ....
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...The use of the symbol u for the control variable s seems also to date from Pontryagin’s work, as the word “control” is “upravlenie” in Russian Gamkrelidze, 1999 ....
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01 Jan 1999
TL;DR: Fuzzy Logic Applications in Mobile Robotics A. Ollero, et al., and Intelligent Data Analysis and Fuzzy Control H.-J.
Abstract: Preface. Part I: The Position and State of the Art of Fuzzy Systems. 1. Fuzzy Systems in Control Engineering H.B. Verbruggen, P.M. Bruijn. 2. Fuzzy Logic, Control Engineering and Artificial Intelligence D. Dubois, et al. 3. Fuzzy Control Versus Conventional Control K.-E. Arzen, et al. 4. Data-Driven Construction of Transparent Fuzzy Models R. Babuska, M. Setnes. Part II: Design and Analysis Issues. 5. Fuzzy Logic Normal Forms for Control Law Representation I. Perfilieva. 6. Stability Analysis of Fuzzy Control Loops A. Ollero, et al. 7. Performance Criteria: Classical and Fuzzy Design J.M. Sousa, et al. 8. Complexity Reduction Methods for Fuzzy Systems M. Setnes, et al. Part III: Application of Fuzzy Systems. 9. Intelligent Data Analysis and Fuzzy Control H.-J. Zimmermann, et al. 10. Fuzzy Control in Process Industry E.K. Juuso. 11. Fuzzy Logic Applications in Mobile Robotics A. Ollero, et al. 12. Enhancing Flight Control using Fuzzy Logic G. Schram, et al. References. Index.
51 citations