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Richard H. Middleton

Bio: Richard H. Middleton is an academic researcher from University of Newcastle. The author has contributed to research in topics: Control theory & Linear system. The author has an hindex of 48, co-authored 393 publications receiving 12037 citations. Previous affiliations of Richard H. Middleton include Hamilton Institute & University of California.


Papers
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Journal ArticleDOI
TL;DR: A lower bound on the performance achievable at a specified terminal time using nonlinear time-varying communication and control strategies is discussed and it is shown that this bound may be achieved using strategies that are linear.
Abstract: We consider the problem of minimizing the response of a plant output to a stochastic disturbance using a control law that relies on the output of a noisy communication channel. We discuss a lower bound on the performance achievable at a specified terminal time using nonlinear time-varying communication and control strategies and show that this bound may be achieved using strategies that are linear. We also consider strategies that are defined over an infinite horizon that may achieve better transient response that those that are optimal for the terminal time problem.

69 citations

Journal ArticleDOI
TL;DR: In this article, the steady-state response of a hybrid feedback system to a sinusoidal input is considered and a theory of design limitations for sampled-data feedback systems wherein the response of the analogue system output is considered.
Abstract: There is a well-developed theory describing inherent design limitations for linear time invariant feedback systems consisting of an analogue plant and analogue controller. This theory describes limitations on achievable performance present when the plant has non-minimum phase zeros, unstable poles, and/or time delays. The parallel theory for linear time invariant discrete time systems is less interesting because it describes system behaviour only at sampling instants. This paper develops a theory of design limitations for sampled-data feedback systems wherein the response of the analogue system output is considered. This is done using the fact that the steady-state response of a hybrid feedback system to a sinusoidal input consists of a fundamental component at the frequency of the input together with infinitely many harmonics at frequencies spaced integer multiples of the sampling frequency away from the fundamental. This fact allows fundamental sensitivity and complementary sensitivity functions that re...

69 citations

Journal ArticleDOI
TL;DR: It is shown that the existence of a negative semidefinite solution together with simple additional conditions is sufficient to guarantee asymptotic stability and can be used to study a wider range of dynamical systems, including systems with singularities on the stability boundary (SSB), which cannot be exponentially stable.
Abstract: This paper gives results on stability and asymptotic stability of two-dimensional systems using linear matrix inequalities (LMIs). Despite a long history of research in this area, systems with singularities on the stability boundary (SSB) have received limited attention because they cannot produce a sign definite solution to the required LMI. However, 2D systems describing some classes of models of vehicle platoons generically involve an SSB. Therefore, commonly used definitions for (asymptotic) stability and strict LMI conditions are not suitable to discuss the stability of these systems. It is shown that the existence of a negative semidefinite solution together with simple additional conditions is sufficient to guarantee asymptotic stability. Thus, the stability conditions discussed here can be used to study a wider range of dynamical systems, including systems with singularities on the stability boundary (SSB), which cannot be exponentially stable. A unified framework is used to analyse continuous-continuous, continuous-discrete and discrete-discrete systems simultaneously.

68 citations

Journal ArticleDOI
TL;DR: In this article, the authors locate repetition within an overall theory of musical syntax and posit two structural types: the monad (the circular, the mythic, the blank space: most nearly approached by silence or by a single, unchanging, unending sound); and the infinite set* (the linear, the narrative, the replete process: most near * The term is taken from mathematical set theory).
Abstract: Repetition, as a component of musical structure in popular songs, has long played an important part in 'popular common-sense' definitions, and criticisms, of the music. 'It's monotonous'; 'it's all the same'; 'it's predictable': such reactions have probably filtered down from the discussions of mass culture theorists. From this point of view, repetition (within a song) can be assimilated to the same category as what Adorno termed standardisation (as between songs). Of course, the significance of the role played by such techniques in the operations of the music industry - their efficacy in helping to define and hold markets, to channel types of consumption, to pre-form response and to make listening easy - can hardly be denied; it is, however, equally difficult to reduce the function of repetition simply to an analysis of the 'political economy' of popular music production and its ideological effects. Despite Adorno's critical assault (see Adorno 1941), despite later twists to the theory by, for instance, Fredric Jameson (1981), who argues that rather than being a negative quality of mass culture, repetition is simply a fundamental characteristic of all cultural production under contemporary capitalism, the question of repetition refuses to go away. Why do listeners find interest and pleasure in hearing the same thing over again? To be able to answer this question, which has troubled not only mass cultural theory but also traditional philosophical aesthetics, as well as more recent approaches such as psychoanalysis and information theory, would tell us more about the nature of popular music, and hence, mutatis mutandis, about music in general, than almost anything else. We must start by locating repetition within an overall theory of musical syntax. Repetition in musical syntax Analytically, we can posit two (ideal) structural types: the monad (the circular, the 'mythic', the blank space: most nearly approached by silence or by a single, unchanging, unending sound); and the infinite set* (the linear, the 'narrative', the replete process: most nearly * The term is taken from mathematical set theory.

66 citations

Journal ArticleDOI
TL;DR: This paper shows how the precompensator can be designed adaptively using input-output measurements and shows that the adaptive scheme will converge provided the system is persistently excited and a suitable model structure is used in the estimation.
Abstract: For many industrial processes, it is of interest to design a decoupling precompensator. The precompensator makes it possible to design controllers based on single-input-single-output models of the process. A model of the process must be known to design the precompensator. This paper shows how the precompensator can be designed adaptively using input-output measurements. The precompensator is first designed for the case when the process is known. The adaptive precompensator is then constructed using the certainty equivalence principle. The convergence properties and the implementation of the adaptive decoupler are discussed. It is shown that the adaptive scheme will converge provided the system is persistently excited and that a suitable model structure is used in the estimation.

64 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
01 Apr 1988-Nature
TL;DR: In this paper, a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) is presented.
Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

9,929 citations

Journal ArticleDOI
06 Jun 1986-JAMA
TL;DR: The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or her own research.
Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

7,563 citations

Proceedings ArticleDOI
15 Oct 1995
TL;DR: In this article, the authors present a model for dynamic control systems based on Adaptive Control System Design Steps (ACDS) with Adaptive Observers and Parameter Identifiers.
Abstract: 1. Introduction. Control System Design Steps. Adaptive Control. A Brief History. 2. Models for Dynamic Systems. Introduction. State-Space Models. Input/Output Models. Plant Parametric Models. Problems. 3. Stability. Introduction. Preliminaries. Input/Output Stability. Lyapunov Stability. Positive Real Functions and Stability. Stability of LTI Feedback System. Problems. 4. On-Line Parameter Estimation. Introduction. Simple Examples. Adaptive Laws with Normalization. Adaptive Laws with Projection. Bilinear Parametric Model. Hybrid Adaptive Laws. Summary of Adaptive Laws. Parameter Convergence Proofs. Problems. 5. Parameter Identifiers and Adaptive Observers. Introduction. Parameter Identifiers. Adaptive Observers. Adaptive Observer with Auxiliary Input. Adaptive Observers for Nonminimal Plant Models. Parameter Convergence Proofs. Problems. 6. Model Reference Adaptive Control. Introduction. Simple Direct MRAC Schemes. MRC for SISO Plants. Direct MRAC with Unnormalized Adaptive Laws. Direct MRAC with Normalized Adaptive Laws. Indirect MRAC. Relaxation of Assumptions in MRAC. Stability Proofs in MRAC Schemes. Problems. 7. Adaptive Pole Placement Control. Introduction. Simple APPC Schemes. PPC: Known Plant Parameters. Indirect APPC Schemes. Hybrid APPC Schemes. Stabilizability Issues and Modified APPC. Stability Proofs. Problems. 8. Robust Adaptive Laws. Introduction. Plant Uncertainties and Robust Control. Instability Phenomena in Adaptive Systems. Modifications for Robustness: Simple Examples. Robust Adaptive Laws. Summary of Robust Adaptive Laws. Problems. 9. Robust Adaptive Control Schemes. Introduction. Robust Identifiers and Adaptive Observers. Robust MRAC. Performance Improvement of MRAC. Robust APPC Schemes. Adaptive Control of LTV Plants. Adaptive Control for Multivariable Plants. Stability Proofs of Robust MRAC Schemes. Stability Proofs of Robust APPC Schemes. Problems. Appendices. Swapping Lemmas. Optimization Techniques. Bibliography. Index. License Agreement and Limited Warranty.

4,378 citations