Covering deterministic scheduling, stochastic scheduling, and the probabilistic analysis of algorithms, this unusually broad view of the subject brings together tutorials, surveys and articles with original results from foremost international experts. The contributions reflect the great diversity in scheduling theory in terms of academic disciplines, applications areas, fundamental approaches and mathematical skills. This book will help researchers to be aware of the progress in the various areas of specialization and the possible influences that this progress may have on their own specialities. Few disciplines are driven so much by continually changing and expanding technology, a fact that gives scheduling a permanence while adding to the excitement of designing and analyzing new systems. The book will be a vital resource for researchers and graduate students of computer science, applied mathematics and operational research who wish to remain up-to-date on the scheduling models and problems of many of the newest technologies in industry, commerce, and the computer and communications sciences.

This book helps students, researchers, and practicing engineers to understand the theoretical framework of control and system theory for discrete-time stochastic systems so that they can then apply its principles to their own stochastic control systems and to the solution of control, filtering, and realization problems for such systems. Applications of the theory in the book include the control of ships, shock absorbers, traffic and communications networks, and power systems with fluctuating power flows. The focus of the book is a stochastic control system defined for a spectrum of probability distributions including Bernoulli, finite, Poisson, beta, gamma, and Gaussian distributions. The concepts of observability and controllability of a stochastic control system are defined and characterized. Each output process considered is, with respect to conditions, represented by a stochastic system called a stochastic realization. The existence of a control law is related to stochastic controllability while the existence of a filter system is related to stochastic observability. Stochastic control with partial observations is based on the existence of a stochastic realization of the filtration of the observed process.

This thesis reports on novel methods for gain-scheduling and fault tolerant control (FTC). It begins by analyzing the connection between the linear parameter varying (LPV) and Takagi-Sugeno (TS) paradigms. This is then followed by a detailed description of the design of robust and shifting state-feedback controllers for these systems. Furthermore, it presents two approaches to fault-tolerant control: the first is based on a robust polytopic controller design, while the second involves a reconfiguration of the reference model and the addition of virtual actuators into the loop. Inaddition the thesis offers a thorough review of the state-of-the art in gain scheduling and fault-tolerant control, with a special emphasis on LPV and TS systems.

This book focuses on modern technologies and systems for solving problems in the energy sector. It is shown that bioenergy is one of the promising areas of energy development. The book collected the experience of scientists from many countries in the research of renewable energy. The advantages of renewable energy are general availability, renewability, environmental friendliness. The analysis carried out by the authors shows the current state of renewable energy in the world, its trends and prospects. New measuring systems are presented, which can become the basis for measuring the thermal characteristics of various types of fuels, including biofuels, insulating materials, enclosing structures, etc. System for monitoring of grainy biomass comminution with the use of genetic algorithms has been presented and described. New technologies for the construction of power plants based on renewable energy sources have been proposed and investigated.

Niklas Luhmann ranks as one of the most important sociologists and social theorists of the twentieth century. Through his many books he developed a highly original form of systems theory that has been hugely influential in a wide variety of disciplines.

In "Introduction to Systems Theory," Luhmann explains the key ideas of general and sociological systems theory and supplies a wealth of examples to illustrate his approach. The book offers a wide range of concepts and theorems that can be applied to politics and the economy, religion and science, art and education, organization and the family. Moreover, Luhmann's ideas address important contemporary issues in such diverse fields as cognitive science, ecology, and the study of social movements.

This book provides all the necessary resources for readers to work through the foundations of systems theory - no other work by Luhmann is as clear and accessible as this. There is also much here that will be of great interest to more advanced scholars and practitioners in sociology and the social sciences.

This book provides energy efficiency quantitative analysis and optimal methods for discrete manufacturing systems from the perspective of global optimization. In order to analyze and optimize energy efficiency for discrete manufacturing systems, it uses real-time access to energy consumption information and models of the energy consumption, and constructs an energy efficiency quantitative index system. Based on the rough set and analytic hierarchy process, it also proposes a principal component quantitative analysis and a combined energy efficiency quantitative analysis. In turn, the book addresses the design and development of quantitative analysis systems. To save energy consumption on the basis of energy efficiency analysis, it presents several optimal control strategies, including one for single-machine equipment, an integrated approach based on RWA-MOPSO, and one for production energy efficiency based on a teaching and learning optimal algorithm. Given its scope, the book offers a valuable guide for students, teachers, engineers and researchers in the field of discrete manufacturing systems.

This book presents recent advances in control and filter design for Takagi-Sugeno (T-S) fuzzy systems with switched parameters. Thanks to its powerful ability in transforming complicated nonlinear systems into a set of linear subsystems, the T-S fuzzy model has received considerable attention from those the field of control science and engineering. Typical applications of T-S fuzzy systems include communication networks, and mechanical and power electronics systems. Practical systems often experience abrupt variations in their parameters or structures due to outside disturbances or component failures, and random switching mechanisms have been used to model these stochastic changes, such as the Markov jump principle. There are three general types of controller/filter for fuzzy Markov jump systems: mode-independent, mode-dependent and asynchronous. Mode-independence does not focus on whether modes are accessible and ignores partially useful mode information, which results in some conservatism. The mode-dependent design approach relies on timely, complete and correct information regarding the mode of the studied plant. Factors like component failures and data dropouts often make it difficult to obtain exact mode messages, which further make the mode-dependent controllers/filters less useful. Recently, to overcome these issues, researchers have focused on asynchronous techniques. Asynchronous modes are accessed by observing the original systems based on certain probabilities. The book investigates the problems associated with controller/filter design for all three types. It also considers various networked constraints, such as data dropouts and time delays, and analyzes the performances of the systems based on Lyapunov function and matrix inequality techniques, including the stochastic stability, dissipativity, and $H_\infty$. The book not only shows how these approaches solve the control and filtering problems effectively, but also offers potential meaningful research directions and ideas. Covering a variety of fields, including continuous-time and discrete-time Markov processes, fuzzy systems, robust control, and filter design problems, the book is primarily intended for researchers in system and control theory, and is also a valuable reference resource for graduate and undergraduate students. Further, it provides cases of fuzzy control problems that are of interest to scientists, engineers and researchers in the field of intelligent control. Lastly it is useful for advanced courses focusing on fuzzy modeling, analysis, and control.

This book introduces iterative learning control (ILC) and its applications to the new equations such as fractional order equations, impulsive equations, delay equations, and multi-agent systems, which have not been presented in other books on conventional fields. ILC is an important branch of intelligent control, which is applicable to robotics, process control, and biological systems. The fractional version of ILC updating laws and formation control are presented in this book. ILC design for impulsive equations and inclusions are also established. The broad variety of achieved results with rigorous proofs and many numerical examples make this book unique. This book is useful for graduate students studying ILC involving fractional derivatives and impulsive conditions as well as for researchers working in pure and applied mathematics, physics, mechanics, engineering, biology, and related disciplines.

During the last decade, the area of stochastic max-plus linear systems has witnessed a rapid development, which created a growing interest in this area. This book provides a thorough treatment of the theory of stochastic max-plus linear systems. Max-plus algebra is an algebraic approach to discrete event systems (DES), like queuing networks that are prone to synchronization. Perturbation analysis studies the sensitivity of the performance of DES with respect to changes in a particular system parameter. The first part of the book addresses modeling issues and stability theory for stochastic max-plus systems. The second part of the book treats perturbation analysis of max-plus systems: a calculus for differentiation of max-plus systems is developed. This calculus leads to numerical evaluations of performance indices of max-plus linear stochastic systems, such as the Lyapunov exponent or waiting times.

This book features selected manuscripts presented at ICoNSoM 2019, exploring cutting-edge methods for developing novel models in nonlinear solid mechanics. Innovative methods like additive manufacturing-for example, 3D printing- and miniaturization mean that engineers need more accurate techniques for modeling solid body mechanics. The book focuses on the formulation of continuum and discrete models for complex materials and systems, particularly the design of metamaterials.

This book introduces readers to using the simple but effective Zhang-gradient (ZG) method to solve tracking-control problems concerning various nonlinear systems, while also highlighting the applications of the ZG method to tracking control for practical systems, e.g. an inverted-pendulum-on-a-cart (IPC) system and a two-wheeled mobile robot (showing its potential applications). In addition to detailed theoretical analyses of ZG controllers, the book presents a wealth of computer simulations to demonstrate the feasibility and efficacy of the controllers discussed (as well as the method itself). More importantly, the superiority of ZG controllers in overcoming the division-by-zero (DBZ) problem is also illustrated. Given its scope and format, the book is well suited for undergraduate and graduate students, as well as academic and industrial researchers in the fields of neural dynamics/neural networks, nonlinear control, computer mathematics, time-varying problem solving, modeling and simulation, analog hardware, and robotics.

Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.

This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user's perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.

This monograph presents a simple and efficient two-relay control algorithm for generation of self-excited oscillations of a desired amplitude and frequency in dynamic systems. Developed by the authors, the two-relay controller consists of two relays switched by the feedback received from a linear or nonlinear system, and represents a new approach to the self-generation of periodic motions in underactuated mechanical systems. The first part of the book explains the design procedures for two-relay control using three different methodologies - the describing-function method, Poincare maps, and the locus-of-a perturbed-relay-system method - and concludes with stability analysis of designed periodic oscillations. Two methods to ensure the robustness of two-relay control algorithms are explored in the second part, one based on the combination of the high-order sliding mode controller and backstepping, and the other on higher-order sliding-modes-based reconstruction of uncertainties and their compensation where Lyapunov-based stability analysis of tracking error is used. Finally, the third part illustrates applications of self-oscillation generation by a two-relay control with a Furuta pendulum, wheel pendulum, 3-DOF underactuated robot, 3-DOF laboratory helicopter, and fixed-phase electronic circuits. Self-Oscillations in Dynamic Systems will appeal to engineers, researchers, and graduate students working on the tracking and self-generation of periodic motion of electromechanical systems, including non-minimum-phase systems. It will also be of interest to mathematicians working on analysis of periodic solutions.

This book contains all refereed papers that were accepted to the third edition of the -Complex Systems Design & Management- (CSD&M 2012) international conference that took place in Paris (France) from December 12-14, 2012.

(Website: http: //www.csdm2012.csdm.fr)

These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (transport, defense & security, electronics, energy & environment, e-services), scientific & technical topics (systems fundamentals, systems architecture& engineering, systems metrics & quality, systemic tools) and system types (transportation systems, embedded systems, software & information systems, systems of systems, artificial ecosystems).

The CSD&M 2012 conference is organized under the guidance of the CESAMES non-profit organization (http: //www.cesames.net)."

This book aims to bring together the latest innovative knowledge, analysis, and synthesis of fractional control problems of nonlinear systems as well as some related applications. Fractional order systems (FOS) are dynamical systems that can be modelled by a fractional differential equation carried with a non-integer derivative. In the last few decades, the growth of science and engineering systems has considerably stimulated the employment of fractional calculus in many subjects of control theory, for example, in stability, stabilization, controllability, observability, observer design, and fault estimation. The application of control theory in FOS is an important issue in many engineering applications. So, to accurately describe these systems, the fractional order differential equations have been introduced.

This monograph provides a comprehensive analysis of the control of singularly perturbed time delay systems. Expanding on the author's previous work on controllability of linear systems with delays in the state and control variables, this volume's comprehensive coverage makes it a valuable addition to the field. Each chapter is self-contained, allowing readers to study them independently or in succession. After a brief introduction, the book systematically examines properties of different classes of singularly perturbed time delay systems, including linear time-dependent systems with multiple point-wise and distributed state delays. The author then considers more general singularly perturbed systems with state and control delays. Euclidean space controllability for all of these systems is also discussed, using numerous examples from real-life models throughout the text to illustrate the results presented. More technically complicated proofs are presented in separate subsections. The final chapter includes a section dedicated to non-linear time delay systems. This book is ideal for researchers, engineers, and graduate students in systems science and control theory. Other applied mathematicians and researchers working in biology and medicine will also find this volume to be a valuable resource.

This book studies selected discrete-time flight control schemes for fixed-wing unmanned aerial vehicle (UAV) systems in the presence of system uncertainties, external disturbances and input saturation. The main contributions of this book for UAV systems are as follows: (i) the proposed integer-order discrete-time control schemes are based on the designed discrete-time disturbance observers (DTDOs) and the neural network (NN); and (ii) the fractional-order discrete-time control schemes are developed by using the fractional-order calculus theory, the NN and the DTDOs. The book offers readers a good understanding of how to establish discrete-time tracking control schemes for fixed-wing UAV systems subject to system uncertainties, external wind disturbances and input saturation. It represents a valuable reference guide for academic research on uncertain UAV systems, and can also support advanced / Ph.D. studies on control theory and engineering.

This book offers a short and concise introduction to the many facets of chaos theory. While the study of chaotic behavior in nonlinear, dynamical systems is a well-established research field with ramifications in all areas of science, there is a lot to be learnt about how chaos can be controlled and, under appropriate conditions, can actually be constructive in the sense of becoming a control parameter for the system under investigation, stochastic resonance being a prime example. The present work stresses the latter aspects and, after recalling the paradigm changes introduced by the concept of chaos, leads the reader skillfully through the basics of chaos control by detailing the relevant algorithms for both Hamiltonian and dissipative systems, among others. The main part of the book is then devoted to the issue of synchronization in chaotic systems, an introduction to stochastic resonance, and a survey of ratchet models. In this second, revised and enlarged edition, two more chapters explore the many interfaces of quantum physics and dynamical systems, examining in turn statistical properties of energy spectra, quantum ratchets, and dynamical tunneling, among others. This text is particularly suitable for non-specialist scientists, engineers, and applied mathematical scientists from related areas, wishing to enter the field quickly and efficiently. From the reviews of the first edition: This book is an excellent introduction to the key concepts and control of chaos in (random) dynamical systems [...] The authors find an outstanding balance between main physical ideas and mathematical terminology to reach their audience in an impressive and lucid manner. This book is ideal for anybody who would like to grasp quickly the main issues related to chaos in discrete and continuous time. Henri Schurz, Zentralblatt MATH, Vol. 1178, 2010.

With contributions from a number of pioneering researchers in the field, this collection is aimed not only at researchers and scientists in nonlinear dynamics but also at a broader audience interested in understanding and exploring how modern chaos theory has developed since the days of Poincare. This book was motivated by and is an outcome of the CHAOS 2015 meeting held at the Henri Poincare Institute in Paris, which provided a perfect opportunity to gain inspiration and discuss new perspectives on the history, development and modern aspects of chaos theory. Henri Poincare is remembered as a great mind in mathematics, physics and astronomy. His works, well beyond their rigorous mathematical and analytical style, are known for their deep insights into science and research in general, and the philosophy of science in particular. The Poincare conjecture (only proved in 2006) along with his work on the three-body problem are considered to be the foundation of modern chaos theory.

This book presents a snapshot of the state-of-art in the field of turbulence modeling, with an emphasis on numerical methods. Topics include direct numerical simulations, large eddy simulations, compressible turbulence, coherent structures, two-phase flow simulation and many more. It includes both theoretical contributions and experimental works, as well as chapters derived from keynote lectures, presented at the fourth Turbulence and Interactions Conference (TI 2015), which was held on June 11-14 in Cargese, Corsica, France. This multifaceted collection, which reflects the conferences emphasis on the interplay of theory, experiments and computing in the process of understanding and predicting the physics of complex flows and solving related engineering problems, offers a timely guide for students, researchers and professionals in the field of applied computational fluid dynamics, turbulence modeling and related areas.

This volume contains the proceedings of the 5th International Conference on Frontier Computing (FC 2016), Tokyo, Japan, July 13-15, 2016. This international meeting provided a forum for researchers to share current understanding of recent advances and emergence in information technology, science, and engineering, with themes in the scope of Communication Networks, Business Intelligence and Knowledge Management, Web Intelligence, and any related fields that further the development of information technology. The articles presented cover a wide spectrum of topics: database and data mining, networking and communications, web and internet of things, embedded system, soft computing, social network analysis, security and privacy, optics communication, and ubiquitous/pervasive computing. Many papers report results of great academic potential and value, and in addition, indicate promising directions of research in the focused realm of this conference series. Readers, including students, academic researchers, and professionals, will benefit from the results presented in this book. It also provides an overview of current research and can be used as a guidebook for those new to the field.

This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.

Cooperative Control of Nonlinear Networked Systems is concerned with the distributed cooperative control of multiple networked nonlinear systems in the presence of unknown non-parametric uncertainties and non-vanishing disturbances under certain communication conditions. It covers stability analysis tools and distributed control methods for analyzing and synthesizing nonlinear networked systems. The book presents various solutions to cooperative control problems of multiple networked nonlinear systems on graphs. The book includes various examples with segments of MATLAB (R) codes for readers to verify, validate, and replicate the results. The authors present a series of new control results for nonlinear networked systems subject to both non-parametric and non-vanishing uncertainties, including the cooperative uniformly ultimately bounded (CUUB) result, finite-time stability result, and finite-time cooperative uniformly ultimately bounded (FT-CUUB) result. With some mathematical tools, such as algebraic graph theory and certain aspects of matrix analysis theory introduced by the authors, the readers can obtain a deeper understanding of the roles of matrix operators as mathematical machinery for cooperative control design for multi-agent systems. Cooperative Control of Nonlinear Networked Systems is a valuable source of information for researchers and engineers in cooperative adaptive control, as its technical contents are presented with examples in full analytical and numerical detail, and graphically illustrated for easy-to-understand results. Scientists in research institutes and academics in universities working on nonlinear systems, adaptive control and distributed control will find the book of interest, as it contains multi-disciplinary problems and covers different areas of research.

This book provides a series of systematic theoretical results and numerical solution algorithms for dynamic optimization problems of switched systems within infinite-dimensional inequality path constraints. Dynamic optimization of path-constrained switched systems is a challenging task due to the complexity from seeking the best combinatorial optimization among the system input, switch times and switching sequences. Meanwhile, to ensure safety and guarantee product quality, path constraints are required to be rigorously satisfied (i.e., at an infinite number of time points) within a finite number of iterations. Several novel methodologies are presented by using dynamic optimization and semi-infinite programming techniques. The core advantages of our new approaches lie in two folds: i) The system input, switch times and the switching sequence can be optimized simultaneously. ii) The proposed algorithms terminate within finite iterations while coming with a certification of feasibility for the path constraints. In this book, first, we provide brief surveys on dynamic optimization of path-constrained systems and switched systems. For switched systems with a fixed switching sequence, we propose a bi-level algorithm, in which the input is optimized at the inner level, and the switch times are updated at the outer level by using the gradient information of the optimal value function calculated at the optimal input. We then propose an efficient single-level algorithm by optimizing the input and switch times simultaneously, which greatly reduces the number of nonlinear programs and the computational burden. For switched systems with free switching sequences, we propose a solution framework for dynamic optimization of path-constrained switched systems by employing the variant 2 of generalized Benders decomposition technique. In this framework, we adopt two different system formulations in the primal and master problem construction and explicitly characterize the switching sequences by introducing a binary variable. Finally, we propose a multi-objective dynamic optimization algorithm for locating approximated local Pareto solutions and quantitatively analyze the approximation optimality of the obtained solutions. This book provides a unified framework of dynamic optimization of path-constrained switched systems. It can therefore serve as a useful book for researchers and graduate students who are interested in knowing the state of the art of dynamic optimization of switched systems, as well as recent advances in path-constrained optimization problems. It is a useful source of up-to-date optimization methods and algorithms for researchers who study switched systems and graduate students of control theory and control engineering. In addition, it is also a useful source for engineers who work in the control and optimization fields such as robotics, chemical engineering and industrial processes.