Deterministic Artificial Intelligence

Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Euler’s moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation. The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book

Digital Filters

The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

Feedback Systems: An Introduction for Scientists and Engineers

This book provides an introduction to the basic principles and tools for the design and analysis of feedback systems. It is intended to serve a diverse audience of scientists and engineers who are interested in understanding and utilizing feedback in physical, biological, information and social systems.We have attempted to keep the mathematical prerequisites to a minimum while being careful not to sacrifice rigor in the process. We have also attempted to make use of examples from a variety of disciplines, illustrating the generality of many of the tools while at the same time showing how they can be applied in specific application domains. A major goal of this book is to present a concise and insightful view of the current knowledge in feedback and control systems. The field of control started by teaching everything that was known at the time and, as new knowledge was acquired, additional courses were developed to cover new techniques. A consequence of this evolution is that introductory courses have remained the same for many years, and it is often necessary to take many individual courses in order to obtain a good perspective on the field. In developing this book, we have attempted to condense the current knowledge by emphasizing fundamental concepts. We believe that it is important to understand why feedback is useful, to know the language and basic mathematics of control and to grasp the key paradigms that have been developed over the past half century. It is also important to be able to solve simple feedback problems using back-of-the-envelope techniques, to recognize fundamental limitations and difficult control problems and to have a feel for available design methods. This book was originally developed for use in an experimental course at Caltech involving students from a wide set of backgrounds. The course was offered to undergraduates at the junior and senior levels in traditional engineering disciplines, as well as first- and second-year graduate students in engineering and science. This latter group included graduate students in biology, computer science and physics. Over the course of several years, the text has been classroom tested at Caltech and at Lund University, and the feedback from many students and colleagues has been incorporated to help improve the readability and accessibility of the material. Because of its intended audience, this book is organized in a slightly unusual fashion compared to many other books on feedback and control. In particular, we introduce a number of concepts in the text that are normally reserved for second-year courses on control and hence often not available to students who are not control systems majors. This has been done at the expense of certain traditional topics, which we felt that the astute student could learn independently and are often explored through the exercises. Examples of topics that we have included are nonlinear dynamics, Lyapunov stability analysis, the matrix exponential, reachability and observability, and fundamental limits of performance and robustness. Topics that we have deemphasized include root locus techniques, lead/lag compensation and detailed rules for generating Bode and Nyquist plots by hand. Several features of the book are designed to facilitate its dual function as a basic engineering text and as an introduction for researchers in natural, information and social sciences. The bulk of the material is intended to be used regardless of the audience and covers the core principles and tools in the analysis and design of feedback systems. Advanced sections, marked by the “dangerous bend” symbol shown here, contain material that requires a slightly more technical background, of the sort that would be expected of senior undergraduates in engineering. A few sections are marked by two dangerous bend symbols and are intended for readers with more specialized backgrounds, identified at the beginning of the section. To limit the length of the text, several standard results and extensions are given in the exercises, with appropriate hints toward their solutions. To further augment the printed material contained here, a companion web site has been developed and is available from the publisher’s web page: http://press.princeton.edu/titles/8701.html The web site contains a database of frequently asked questions, supplemental examples and exercises, and lecture material for courses based on this text. The material is organized by chapter and includes a summary of the major points in the text as well as links to external resources. The web site also contains the source code for many examples in the book, as well as utilities to implement the techniques described in the text. Most of the code was originally written using MATLAB M-files but was also tested with LabView MathScript to ensure compatibility with both packages. Many files can also be run using other scripting languages such as Octave, SciLab, SysQuake and Xmath. The first half of the book focuses almost exclusively on state space control systems. We begin in Chapter 2 with a description of modeling of physical, biological and information systems using ordinary differential equations and difference equations. Chapter 3 presents a number of examples in some detail, primarily as a reference for problems that will be used throughout the text. Following this, Chapter 4 looks at the dynamic behavior of models, including definitions of stability and more complicated nonlinear behavior. We provide advanced sections in this chapter on Lyapunov stability analysis because we find that it is useful in a broad array of applications and is frequently a topic that is not introduced until later in one’s studies. The remaining three chapters of the first half of the book focus on linear systems, beginning with a description of input/output behavior in Chapter 5. In Chapter 6, we formally introduce feedback systems by demonstrating how state space control laws can be designed. This is followed in Chapter 7 by material on output feedback and estimators. Chapters 6 and 7 introduce the key concepts of reachability and observability, which give tremendous insight into the choice of actuators and sensors, whether for engineered or natural systems. The second half of the book presents material that is often considered to be from the field of “classical control.” This includes the transfer function, introduced in Chapter 8, which is a fundamental tool for understanding feedback systems. Using transfer functions, one can begin to analyze the stability of feedback systems using frequency domain analysis, including the ability to reason about the closed loop behavior of a system from its open loop characteristics. This is the subject of Chapter 9, which revolves around the Nyquist stability criterion. In Chapters 10 and 11, we again look at the design problem, focusing first on proportional-integral-derivative (PID) controllers and then on the more general process of loop shaping. PID control is by far the most common design technique in control systems and a useful tool for any student. The chapter on frequency domain design introduces many of the ideas of modern control theory, including the sensitivity function. In Chapter 12, we combine the results from the second half of the book to analyze some of the fundamental trade-offs between robustness and performance. This is also a key chapter illustrating the power of the techniques that have been developed and serving as an introduction for more advanced studies. The book is designed for use in a 10- to 15-week course in feedback systems that provides many of the key concepts needed in a variety of disciplines. For a 10-week course, Chapters 1–2, 4–6 and 8–11 can each be covered in a week’s time, with the omission of some topics from the final chapters. A more leisurely course, spread out over 14–15 weeks, could cover the entire book, with 2 weeks on modeling (Chapters 2 and 3) — particularly for students without much background in ordinary differential equations — and 2 weeks on robust performance (Chapter 12). The mathematical prerequisites for the book are modest and in keeping with our goal of providing an introduction that serves a broad audience. We assume familiarity with the basic tools of linear algebra, including matrices, vectors and eigenvalues. These are typically covered in a sophomore-level course on the subject, and the textbooks by Apostol [10], Arnold [13] and Strang [187] can serve as good references. Similarly, we assume basic knowledge of differential equations, including the concepts of homogeneous and particular solutions for linear ordinary differential equations in one variable. Apostol [10] and Boyce and DiPrima [42] cover this material well. Finally, we also make use of complex numbers and functions and, in some of the advanced sections, more detailed concepts in complex variables that are typically covered in a junior-level engineering or physics course in mathematical methods. Apostol [9] or Stewart [186] can be used for the basic material, with Ahlfors [6], Marsden and Hoffman [146] or Saff and Snider [172] being good references for the more advanced material. We have chosen not to include appendices summarizing these various topics since there are a number of good books available. One additional choice that we felt was important was the decision not to rely on a knowledge of Laplace transforms in the book. While their use is by far the most common approach to teaching feedback systems in engineering, many students in the natural and information sciences may lack the necessary mathematical background. Since Laplace transforms are not required in any essential way, we have included them only in an advanced section intended to tie things together for students with that background. Of course, we make tremendous use of transfer functions, which we introduce through the notion of response to exponential inputs, an approach we feel is more accessible to a broad array of scientists and engineers. For classes in which students have already had Laplace transforms, it should be quite natural to build on this background in the appropriate sections of the text. Acknowledgments: The authors would like to thank the many people who helped during the preparation of this book. The idea for writing this book came in part from a report on future directions in control [155] to which Stephen Boyd, Roger Brockett, John Doyle and Gunter Stein were major contributors. Kristi Morgansen and Hideo Mabuchi helped teach early versions of the course at Caltech on which much of the text is based, and Steve Waydo served as the head TA for the course taught at Caltech in 2003–2004 and provided numerous comments and corrections. Charlotta Johnsson and Anton Cervin taught from early versions of the manuscript in Lund in 2003–2007 and gave very useful feedback. Other colleagues and students who provided feedback and advice include Leif Andersson, John Carson, K. Mani Chandy, Michel Charpentier, Domitilla Del Vecchio, Kate Galloway, Per Hagander, Toivo Henningsson Perby, Joseph Hellerstein, George Hines, Tore Hägglund, Cole Lepine, Anders Rantzer, Anders Robertsson, Dawn Tilbury and Francisco Zabala. The reviewers for Princeton University Press and Tom Robbins at NI Press also provided valuable comments that significantly improved the organization, layout and focus of the book. Our editor, Vickie Kearn, was a great source of encouragement and help throughout the publishing process. Finally, we would like to thank Caltech, Lund University and the University of California at Santa Barbara for providing many resources, stimulating colleagues and students, and pleasant working environments that greatly aided in the writing of this book

Aplicações De Métodos De Sensoriamento De Vibração Baseados Em Técnicas

Orientadores: Fabiano Fruett, Claudio FloridiaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Sensores à fibra óptica distribuídos têm sido empregados para monitorar vários parâmetros, tais como temperatura, vibração, tensão mecânica, campo magnético e corrente elétrica. Quando comparados a outras técnicas convencionais, tais sensores são vantajosos devido a suas pequenas dimensões, imunidade a interferências eletromagnéticas, alta adaptabilidade, robustez a ambientes nocivos, dentre outros. Sensores acústicos distribuídos em particular são interessantes devido a sua capacidade em serem usados em aplicações tais como monitoração de saúde de estruturas e vigilância de perímetros. Através da análise em frequência da estrutura, por exemplo uma aeronave, uma ponte, um edifício ou mesmo máquinas em uma fábrica, é possível avaliar sua condição e detectar danos e falhas em um estágio primário. Tais soluções podem cobrir ambas as aplicações de detecção de intrusão e monitoração estrutural com mínimas adaptações no sistema sensor. Desta forma, vibrações e distúrbios pequenas estruturas com resolução de dezenas de centímetros e em grandes estruturas ou perímetros com alguns metros de resolução espacial e centenas de quilômetros de alcance podem ser detectadas. Outra característica útil desta solução baseada em fibra óptica é a possibilidade de ser combinada com técnicas de processamento digital de sinais, permitindo a detecção e localização de perturbações rápidas, reconhecimento de padrões de intrusão em tempo real e multiplexação de dados de superfícies estruturais para aplicações SHM. O principal objetivo desta tese é fazer uso desses recursos para empregar técnicas de DAS como soluções de tecnologias- chave para várias aplicações. Neste trabalho, as técnicas de phase-OTDR foram estudadas e as principais contribuições da tese focaram em trazer soluções inovadoras e validações para aplicações de vigilância e vigilância. Este doutorado teve um período sanduíche nas instalações da RISE Acreo AB, Estocolmo, Suécia, onde experimentos foram realizados e foi parte da 42ª Chamada CISB/Saab/CNPqAbstract: Distributed optical fiber sensors have been increasingly employed for monitoring several parameters, such as temperature, vibration, strain, magnetic field and current. When compared to other conventional techniques, these sensors are advantageous due to their small dimensions, lightweight, immunity to electromagnetic interference, high adaptability, robustness to hazardous environments, less complex data multiplexing, the feasibility to be embedded into structures with minimum invasion, the capability to extract data with high resolution from long perimeters using a single optical fiber and detect multiple events along the fiber. In particular, distributed acoustic sensors (DAS) based on optical time domain reflectometry (OTDR), are of high interest, due to their capability to be used in applications such as structural health monitoring (SHM) and perimeter surveillance. Through the frequency analysis of a structure, for instance an aircraft, a bridge, a building or even machines in a workshop, it is possible to evaluate its condition and detect damages and failures at an early stage. Also, OTDR based solutions for vibration monitoring can be easily adapted with minimum setup modifications to detect intrusion in a perimeter, a useful tool for surveillance of military facilities, laboratories, power plants and homeland security. The same OTDR technique can be used as a non-destructive diagnostic tool to evaluate vibrations and disturbances on both small structures with some dozens of centimeters¿ resolution and in big structures or perimeters with some meters of spatial resolution and hundreds of kilometers of reach. Another useful feature of this optical fiber based solution is the possibility to be combined with high-performance digital signal processing techniques, enabling fast disturbance detection and location, real-time intrusion pattern recognition and fast data multiplexing of structure surfaces for SHM applications. The main goal of this thesis is to make use of these features to employ DAS techniques as key enabling technologies solutions for several applications. In this work, OTDR based techniques were studied and the thesis main contributions were focused on bringing innovative solutions and validations for SHM and surveillance applications. This PhD had a sandwich period at Acreo AB, Stockholm, Sweden, where experimental tests were performed and it was part of the 42ª CISB/Saab/CNPq CalDoutoradoEletrônica, Microeletrônica e OptoeletrônicaDoutora em Engenharia Elétrica202816/2015-0CAPESCNP

Dynamic Stability with Artificial Intelligence in Smart Grids

Environmental concerns are among the main drives of the energy transition in power systems. Smart grids are the natural evolution of power systems to become more efficient and sustainable. This modernization coincides with the vast and wide integration of energy generation and storage systems dependent on power electronics. At the same time, the low inertia power electronics, introduce new challenges in power system dynamics. In fact, the synchronisation capabilities of power systems are threatened by the emergence of new oscillations and the displacement of conventional solutions for ensuring the stability of power systems. This necessitates an equal modernization of the methods to maintain the rotor angle stability in the future smart grids. The applications of artificial intelligence in power systems are constantly increasing. The thesis reviews the most relevant works for monitoring, predicting, and controlling the rotor angle stability of power systems and presents a novel controller for power oscillation damping

Dynamic stability with artificial intelligence in smart grids

Environmental concerns are among the main drives of the energy transition in power systems. Smart grids are the natural evolution of power systems to become more efficient and sustainable. This modernization coincides with the vast and wide integration of energy generation and storage systems dependent on power electronics. At the same time, the low inertia power electronics, introduce new challenges in power system dynamics. In fact, the synchronisation capabilities of power systems are threatened by the emergence of new oscillations and the displacement of conventional solutions for ensuring the stability of power systems. This necessitates an equal modernization of the methods to maintain the rotor angle stability in the future smart grids. The applications of artificial intelligence in power systems are constantly increasing. The thesis reviews the most relevant works for monitoring, predicting, and controlling the rotor angle stability of power systems and presents a novel controller for power oscillation damping

Integration of online partial discharge monitoring and defect location in medium-voltage cable networks

Partial discharge (PD) diagnostics is a proven method to assess the condition of underground power cables. PDs are symptomatic for a defect (weak spot) that may evolve into a complete breakdown. A PD induces a small pulse in the conductor(s) and earth screen that propagates through the cable in both directions. In previous research an online PD detection and location system was developed for medium-voltage cables. This system is currently introduced by utilities on an increasingly large scale. This thesis deals with several new challenges that are related to the integration of online PD monitoring in different medium-voltage power cable network configurations. A transmission line model of the power cable is required to enable optimal PD detection. A three-core power cable with common earth screen has multiple coupled propagation modes. The propagation modes are decoupled into a modal solution. A practical method to measure and analyze the cable parameters is developed and validated by measurements on a cable sample. Detailed prediction of multiple reflections was achieved, including the mixing of propagation modes having distinct propagation velocities, validating both the model and the measurement method for three-core cables with common earth screen. The semiconducting layers in a cable with cross-linked polyethylene (XLPE) insulation have a significant influence on the transmission line parameters. Unfortunately, the dielectric properties of these layers are usually unknown and can differ between similar cable types. It is shown that nonetheless the characteristic impedance and propagation velocity of single-core and three-core XLPE cables can be calculated using information available from the cable specifications. The calculated values are validated using pulse response measurements on several cable samples. The accuracy of the calculated characteristic impedance and propagation velocity is 5–10%, which is sufficient for estimating PD pulse shape and amplitude in a cable circuit. The online PD monitoring system was initially developed to be installed on a single cable connection between two consecutive ring-main-units (RMUs). It is more efficient to monitor two or more consecutive cables, with one or more RMUs or substations in between, using a single monitoring system. Models for RMUs and substations are proposed and verified by measurements. The influence of RMUs and substations along the cable under test on the PD detection sensitivity and location accuracy is studied using these models and measurements. The influence of a compact RMU with two connected cables is neglectable if the total cable length is longer than approximately 1km. The longer the total cable length, the smaller the influence of an RMU along the cable under test. An RMU or substation along the cable under test with more than two connected cables introduces a significant signal loss, decreasing the detection sensitivity significantly. The higher the number of connected cables, the higher the signal loss. In the equipment found in some substations and RMUs it is not possible to install a PD measurement unit at a desired location. The models and measurements are used to study the feasibility of a single-sided PD measurement, including PD location, with the problematic RMU/substation at the far end. The study shows that a major part of an incoming pulse reflects on a large RMU/substation with many connected cables. This reflection enables a single-sided PD measurement from the other cable end. A single-sided measurement has the disadvantage that the maximum cable length that can be monitored is halved and that it is sensitive to reflections on joints in the cable under test and other connected cables. Accurate location of PDs in cables, based on arrival times, is imperative for the identification and assessment of defects. Five algorithms that determine the time-of-arrival of pulses are evaluated to investigate which method yields the most accurate location under different circumstances. The methods are evaluated analytically, by simulations, and by measurements on a cable system. From the results the energy criterion method and the phase method show the best performance. The energy criterion is a robust method that achieves location accuracy of 0.5% of the cable length or better. The phase method has a good performance only if the phase shift introduced at the transmission from the cable under test to the RMU is known accurately. For maximum detection sensitivity the PD monitoring system uses matched filters. These filters are constructed using predicted PD waveforms. These predictions are based on a series of online system identification measurements and a standard cable model. Due to signal distortions that are not taken in account in the model, e.g. an RMU along the cable under test, the predictions can be inaccurate, resulting in a sub-optimal PD detection. An automated procedure that creates new signal templates, based on measured PD signals, is proposed and tested on signals measured during online PD measurements on multiple cable systems. The algorithm generated new templates for PD signals and for disturbing pulses. New PD pulse templates for may be used to improve the cable system model. Disturbing pulse templates may be used to improve disturbance rejection by the measurement unit

Predictive Abuse Detection for a PLC Smart Lighting Network Based on Automatically Created Models of Exponential Smoothing

One of the basic elements of a Smart City is the urban infrastructure management system, in particular, systems of intelligent street lighting control. However, for their reliable operation, they require special care for the safety of their critical communication infrastructure. This article presents solutions for the detection of different kinds of abuses in network traffic of Smart Lighting infrastructure, realized by Power Line Communication technology. Both the structure of the examined Smart Lighting network and its elements are described. The article discusses the key security problems which have a direct impact on the correct performance of the Smart Lighting critical infrastructure. In order to detect an anomaly/attack, we proposed the usage of a statistical model to obtain forecasting intervals. Then, we calculated the value of the differences between the forecast in the estimated traffic model and its real variability so as to detect abnormal behavior (which may be symptomatic of an abuse attempt). Due to the possibility of appearance of significant fluctuations in the real network traffic, we proposed a procedure of statistical models update which is based on the criterion of interquartile spacing. The results obtained during the experiments confirmed the effectiveness of the presented misuse detection method