This book is intended for researchers, teachers, and students willing to ex- plore conceptual bridges between the fields of Automatic Control and Power Electronics. The need to bring the two disciplines closer has been felt, for many years, both by Power Electronics specialists and by Automatic Control theorists, as a means of fruitful interaction between the two scientific com- munities.
标签： Techniques Control Design
上传时间： 2020-06-10
上传用户：shancjb
There exist two essentially different approaches to the study of dynamical systems, based on the following distinction: time-continuous nonlinear differential equations ⇋ time-discrete maps One approach starts from time-continuous differential equations and leads to time-discrete maps, which are obtained from them by a suitable discretization of time. This path is pursued, e.g., in the book by Strogatz [Str94]. 1 The other approach starts from the study of time-discrete maps and then gradually builds up to time-continuous differential equations, see, e.g., [Ott93, All97, Dev89, Has03, Rob95]. After a short motivation in terms of nonlinear differential equations, for the rest of this course we shall follow the latter route to dynamical systems theory. This allows a generally more simple way of introducing the important concepts, which can usually be carried over to a more complex and physically realistic context.
标签： Systems_Rainer Introduction Dynamical Klages to
上传时间： 2020-06-10
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This book is an outgrowth of a course developed at Stanford University over the past five years. It is suitable as a self-contained textbook for second-level undergraduates or for first-level graduate students in almost every field that employs quantitative methods. As prerequisites, it is assumed that the student may have had a first course in differential equations and a first course in linear algebra or matrix analysis. These two subjects, however, are reviewed in Chapters 2 and 3, insofar as they are required for later developments.
标签： Introduction_to_Dynamic_Systems
上传时间： 2020-06-10
上传用户：shancjb
n recent years, there have been many books published on power system optimization. Most of these books do not cover applications of artifi cial intelligence based methods. Moreover, with the recent increase of artifi cial intelligence applications in various fi elds, it is becoming a new trend in solving optimization problems in engineering in general due to its advantages of being simple and effi cient in tackling complex problems. For this reason, the application of artifi cial intelligence in power systems has attracted the interest of many researchers around the world during the last two decades. This book is a result of our effort to provide information on the latest applications of artifi cial intelligence to optimization problems in power systems before and after deregulation.
标签： Intelligence Artificial System Power in
上传时间： 2020-06-10
上传用户：shancjb
A kinematically redundant manipulator is a serial robotic arm that has more independently driven joints than are necessary to define the desired pose (position and orientation) of its end-effector. With this definition, any planar manipulator (a manipulator whose end-effector motion is restrained in a plane) with more than three joints is a redundant manipulator. Also, a manipulator whose end-effector can accept aspatialposeisaredundant manipulator ifithas morethan sixindependently driven joints. For example, the manipulator shown in Fig. 1.1 has two 7-DOF arms mounted on a torso with three degrees of freedom (DOFs). This provides 10 DOFs for each arm. Since the end-effector of each arm can have a spatial motion with six DOFs, the arms are redundant.
标签： Autonomous Modeling Planning Robots Path
上传时间： 2020-06-10
上传用户：shancjb
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propa- gation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.
标签： Bishop-Pattern-Recognition-and-Ma chine-Learning
上传时间： 2020-06-10
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Current field forecast verification measures are inadequate, primarily because they compress the comparison between two complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to analysis and contemporaneous forecast fields prove to be an insightful approach to verification problems. DWTs allow both filtering and compact physically interpretable partitioning of fields. These techniques are used to reduce or eliminate noise in the verification process and develop multivariate measures of field forecasting performance that are shown to improve upon existing verification procedures.
标签： field forecast verification
上传时间： 2020-07-22
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An Arduino core for the ATmega328, ATmega168, ATmega88, ATmega48 and ATmega8, all running a [custom version of Optiboot for increased functionality](#write-to-own-flash). This core requires at least Arduino IDE v1.6.2, where v1.8.5+ is recommended. <br/> **This core gives you two extra IO pins if you're using the internal oscillator!** PB6 and PB7 is mapped to [Arduino pin 20 and 21](#pinout).<br/> If you're into "generic" AVR programming, I'm happy to tell you that all relevant keywords are being highlighted by the IDE through a separate keywords file. Make sure to test the [example files](https://github.com/MCUdude/MiniCore/tree/master/avr/libraries/AVR_examples/examples) (File > Examples > AVR C code examples). Try writing a register name, <i>DDRB</i> for instance, and see for yourself!
标签： MiniCore
上传时间： 2021-02-22
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%this is an example demonstrating the Radial Basis Function %if you select a RBF that supports it (Gausian, or 1st or 3rd order %polyharmonic spline), this also calculates a line integral between two %points.
上传时间： 2021-07-02
上传用户：19800358905
This texts contemporary approach focuses on the concepts of linear control systems, rather than computational mechanics. Straightforward coverage includes an integrated treatment of both classical and modern control system methods. The text emphasizes design with discussions of problem formulation, design criteria, physical constraints, several design methods, and implementation of compensators.Discussions of topics not found in other texts--such as pole placement, model matching and robust tracking--add to the texts cutting-edge presentation. Students will appreciate the applications and discussions of practical aspects, including the leading problem in developing block diagrams, noise, disturbances, and plant perturbations. State feedback and state estimators are designed using state variable equations and transfer functions, offering a comparison of the two approaches. The incorporation of MATLAB throughout the text helps students to avoid time-consuming computation and concentrate on control system design and analysis
标签： 控制系统
上传时间： 2021-12-15
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