تحسين النتائح
ترتيب حسب
من
الى
الصفحة 1
الصفحة 1
Linear Systems, Signal Processing and Hypercomplex Analysis ; Chapman University, November 2017
includes contributions originating from a conference held at Chapman University during November 14-19, 2017. It presents original research by experts in signal processing, linear systems, operator theory, complex and hypercomplex analysis and related topics.
Liapunov Functions and Stability in Control Theory
Presents a modern and self-contained treatment of the Liapunov method for stability analysis, in the framework of mathematical nonlinear control theory. A Particular focus is on the problem of the existence of Liapunov functions (converse Liapunov theorems) and their regularity, whose interest is especially motivated by applications to automatic control.
Knowledge Processing with Interval and Soft Computing
In particular, these chapters cover computing techniques for interval linear systems of equations, interval matrix singular-value decomposition, interval function approximation, and decision making with statistical and graph-based data processing. To enable these applications, the book presents a standards-based object-oriented interval computing environment in C++.
Mathematical Methods for Robust and Nonlinear Control : EPSRC Summer School
The underlying theory on which much modern robust and nonlinear control is based can often be dif?cult for the student to grasp. In particular, the mathematical - pects can be problematic for students from a standard engineering background. The EPSRC sponsored Summer School which was held in Leicester in September 2006 attempted to “?ll the gap” in students’ appreciation the theory relevant to several important areas of control. This book is a collection of lecture notes which were p- sented at that workshop and consists of, broadly, two parts. The ?rst nine chapters are devoted to the theory behind several areas of robust and nonlinear control and are aimed at introducing fundamental concepts to the reader. The last six chapters contain detailed case studies which aim to demonstrate the use and effectiveness of these modern techniques in real engineering applications. It is hoped that this book will provide a useful introduction to many of the more common robust and nonlinear control techniques and serve as a valuable reference for the more adept practitioner.
Mathematical Control Theory : An Introduction
Mathematical Control Theory: An Introduction presents, in a mathematically precise manner, a unified introduction to deterministic control theory. With the exception of a few more advanced concepts required for the final part of the book, the presentation requires only a knowledge of basic facts from linear algebra, differential equations, and calculus. In addition to classical concepts and ideas, the author covers the stabilization of nonlinear systems using topological methods, realization theory for nonlinear systems, impulsive control and positive systems, the control of rigid bodies, the stabilization of infinite dimensional systems, and the solution of minimum energy problems.
LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay
A fuzzy system is, in a very broad sense, any fuzzy logic-based system where fuzzy logic can be used either asthebasisfor the representation of different forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse fields of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem’s behavior and build useful mathematical models. Different types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems.
Linear Systems Control : Deterministic and Stochastic Methods
Modern control theory and in particular state space or state variable methods can be adapted to the description of many different systems because it depends strongly on physical modeling and physical intuition. The laws of physics are in the form of differential equations and for this reason, this book concentrates on system descriptions in this form. This means coupled systems of linear or nonlinear differential equations. The physical approach is emphasized in this book because it is most natural for complex systems. It also makes what would ordinarily be a difficult mathematical subject into one which can straightforwardly be understood intuitively and which deals with concepts which engineering and science students are already familiar.
Linear Systems
Linear systems theory plays a broad and fundamental role in electrical, mechanical, chemical and aerospace engineering, communications, and signal processing. A thorough introduction to systems theory with emphasis on control is presented in this self-contained textbook. The book examines the fundamental properties that govern the behavior of systems by developing their mathematical descriptions. Linear time-invariant, time-varying, continuous-time, and discrete-time systems are covered. Rigorous development of classic and contemporary topics in linear systems, as well as extensive coverage of stability and polynomial matrix/fractional representation, provide the necessary foundation for further study of systems and control.
Lagrangian and Hamiltonian Methods for Nonlinear Control 2006 ; Proceedings from the 3rd IFAC Workshop, Nagoya, Japan, July 2006
A Differential-Geometric Approach for Bernstein’s Degrees-of-Freedom Problem.- Nonsmooth Riemannian Optimization with Applications to Sphere Packing and Grasping.- Synchronization of Networked Lagrangian Systems.- An Algorithm to Discretize One-Dimensional Distributed Port Hamiltonian Systems.- Virtual Lagrangian Construction Method for Infinitedimensional Systems with Homotopy Operators.- Direct Discrete-Time Design for Sampled-Data Hamiltonian Control Systems.- Kinematic Compensation in Port-Hamiltonian Telemanipulation.- Interconnection and Damping Assignment Passivity-Based Control of a Four-Tank System.- Towards Power-based Control Strategies for a Class of Nonlinear Mechanical Systems.- Power Shaping Control of Nonlinear Systems: A Benchmark Example.- Total Energy Shaping Control of Mechanical Systems: Simplifying the Matching Equations via Coordinate Changes.- Simultaneous Interconnection and Damping Assignment Passivity–Based Control: Two Practical Examples.
Communication Systems
Presents main concepts of mobile communication systems, both analog and digitalIntroduces concepts of probability, random variables and stochastic processes and their applications to the analysis of linear systemsIncludes five appendices covering Fourier series and transforms, GSM cellular systems and more
Cálculo científico con MATLAB y Octave = Scientific computing with MATLAB and Octave
This textbook is an introduction to Scientific Calculus, illustrating various numerical methods for the computer solution of certain classes of mathematical problems. The authors show how to compute the zeros or integrals of continuous functions, solve linear systems, approximate functions by polynomials, and construct precise approximations for the solution of differential equations. To make the presentation concrete and attractive, the MATLAB programming environment has been adopted as a faithful companion.
Cálculo científico com MATLAB e Octave = Scientific calculus with MATLAB and Octave
Its objective is to present various numerical methods for solving certain mathematical problems on the computer that cannot be treated in a simpler way. Classical issues such as the computation of zeros or integrals of continuous functions, the solving of linear systems, the approximation of functions by polynomials and the construction of precise approximations for solutions of differential equations are addressed. All algorithms are presented in the programming languages MATLAB and Octave, whose main commands and instructions are introduced gradually, aiming in particular at their compatibility in both languages.
Assessment and future directions of nonlinear model predictive control
Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.
Artificial neural networks for the Modelling and Fault Diagnosis of Technical Processes
In this book, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.
Approximate and noisy realization of discrete-time dynamical systems
This monograph deals with approximation and noise cancellation of dynamical systems which include linear and nonlinear input/output relations. It will be of special interest to researchers, engineers and graduate students who have specialized in ?ltering theory and system theory. This monograph provides new results and their extensions which can also be applied to nonlinear dynamical systems.
Algebraic Methods for Nonlinear Control Systems
A self-contained introduction to algebraic control for nonlinear systems suitable for researchers and graduate students.The most popular treatment of control for nonlinear systems is from the viewpoint of differential geometry yet this approach proves not to be the most natural when considering problems like dynamic feedback and realization. Professors Conte, Moog and Perdon develop an alternative linear-algebraic strategy based on the use of vector spaces over suitable fields of nonlinear functions. This algebraic perspective is complementary to, and parallel in concept with, its more celebrated differential-geometric counterpart.Algebraic Methods for Nonlinear Control Systems describes a wide range of results, some of which can be derived using differential geometry but many of which cannot.
Advances in Variable Structure and Sliding Mode Control
Sliding Mode Control is recognized as an efficient tool to design controllers which are robust with respect to uncertainty. The resulting controllers have low sensitivity to plant parameters and perturbations and allow the possibility of decoupling the original plant system into two components of lower dimension. In addition many controllers ensure finite time convergence to the switching surface and can be straightforwardly implemented. However, in addition to this traditional area of exploitation, sliding mode concepts are being increasingly deployed for the design of observers for estimation and identification.
Advanced Topics in Control Systems Theory ; Vol. 328 : Lecture Notes from FAP 2005
"Advanced Topics in Control Systems Theory" contains selected contributions written by lecturers at the third (annual) Formation d’Automatique de Paris (FAP) (Graduate Control School in Paris). Following on from the lecture notes from the second FAP (Volume 311 in the same series) it is addressed to graduate students and researchers in control theory with topics touching on a variety of areas of interest to the control community such as nonlinear optimal control, observer design, stability analysis and structural properties of linear systems. The reader is provided with a well-integrated synthesis of the latest thinking in these subjects without the need for an exhaustive literature review. The internationally known contributors to this volume represent many of the most reputable control centers in Europe.
Adaptive Nonlinear System Identification : The Volterra and Wiener Model Approaches
Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials.After a brief introduction to nonlinear systems and to adaptive system identification, the author presents the discrete Volterra model approach. This is followed by an explanation of the Wiener model approach. Adaptive algorithms using both models are developed. The performance of the two methods are then compared to determine which model performs better for system identification applications.
Adaptive Backstepping Control of Uncertain Systems : Nonsmooth Nonlinearities, Interactions or Time-Variations
This book employs the powerful and popular adaptive backstepping control technology to design controllers for dynamic uncertain systems with non-smooth nonlinearities.
