Explicit Nonlinear Model Predictive Control

This volume covers theoretical advances and developments, computational challenges and tools as well as applications in the area of multi-parametric model based control. Part I is concerned with the

This book gathers together a selection of papers presented at the Joint CTS-HYCON Workshop on Nonlinear and Hybrid Control held at the Paris Sorbonne, France, 10-12 July 2006. The main objective of th

This second edition of Dissipative Systems Analysis and Control has been substantially reorganized to accommodate new material and enhance its pedagogical features. It examines linear and nonlinear s

Fuzzy logic methodology has proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model. Technology based on this methodology is applicabl

Automatic control systems have become essential features in virtually every area of technology, from machine tools to aerospace vehicles. This book is a comprehensive, clearly written introduction to automatic control engineering. The author begins with the fundamentals of modelling mechanical, electrical, and electromechanical systems in the state variable format. The emphasis is on classical feedback control theory and design, and their application to practical electromechanical and aerospace problems. Following a careful grounding in classical control theory, the author introduces modern control theory, including digital control and nonlinear system analysis. Over 230 problems help the reader apply principles discussed in the text to practical engineering situations. Engineering students and practising engineers will find all they need to know about control system analysis and design in this valuable text.

This book 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

An overview of the basic concepts, methods and applications of nonlinear low-dimensional solid state physics based on the Frenkel--Kontorova model and its generalizations. The book covers many importa

Offering an introduction to the theory of impulse control in nonlinear systems, this book is useful as a text for a senior or graduate course. Chapters cover discrete-continuous systems with impulse c

The first model of accelerated psychodynamic therapy to make the theoretical why as important as the formula for how, Fosha's original technique for catalyzing change mandates explicit empathy and ra

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control

The dominant paradigm in modern-day fund management remains the Capital Asset Pricing Model (CAPM). Originally developed in the 1960s as an explanatory and predictive model of capital market behaviour

In some domains of mechanics, physics and control theory boundary value problems arise for nonlinear first order PDEs. A well-known classical result states a sufficiency condition for local existence

Automatic control systems have become essential features in virtually every area of technology, from machine tools to aerospace vehicles. This book is a comprehensive, clearly written introduction to automatic control engineering. The author begins with the fundamentals of modelling mechanical, electrical, and electromechanical systems in the state variable format. The emphasis is on classical feedback control theory and design, and their application to practical electromechanical and aerospace problems. Following a careful grounding in classical control theory, the author introduces modern control theory, including digital control and nonlinear system analysis. Over 230 problems help the reader apply principles discussed in the text to practical engineering situations. Engineering students and practising engineers will find all they need to know about control system analysis and design in this valuable text.

Most systems involved in a chemical process plant are interactive multivariable systems, to control which, the transfer function matrix model is required. This lucid book considers the identification and control of such systems. It discusses open loop and closed loop identification methods, as well as the design of multivariable controllers based on steady state gain matrix. Simple methods for designing controllers based on transfer function matrix model have been reviewed. The design of controllers for non-square systems, and closed loop identification of multivariable unstable systems by the optimization method are also covered. Several simulation examples and exercise problems at the end of each chapter further help the reader consolidate the knowledge gained. This book will be useful to any engineering student, researcher or practitioner who works with interactive, multivariable control systems.

Accountability is a staple of Public Administration scholarship, but scholars have been unsuccessful at developing a predictive model of accountable behavior. Large swaths of research about accountability still focuses on scarcely read annual reports as video footage of police encounters are watched and discussed by citizens regularly. In this Element, we seek to further a predictive model of accountability by understanding the norms and expectations associated with the implementation of Body-Worn Cameras. Specifically, this research examines when police departments release, or do not release, footage to the public and the expectations civilians have about the release of that footage. Indirectly, the norms and expectations associated with this technology have broad implications for societal values and the relationship between civilians and law enforcement. Our findings suggest the relationship between law enforcement and civilians is central to the implementation of this policy, and mo

A bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems Model-Based Processing: An Ap

Nonlinear Systems and Their Remarkable Mathematical Structures aims to describe the recent progress in nonlinear differential equations and nonlinear dynamical systems (both continuous and discrete).

This book presents a tutorial review of van der Pol model, a universal oscillator model for the analysis of modern RC-oscillators in weak and strong nonlinear regimes. A detailed analysis of the injec

The book focuses on how to design general PI/PD/PID controller with self-tuning gains for different systems, which includes SISO nonlinear system, SISO nonaffine system and MIMO nonlinear system. It p

This book guides readers along a path that proceeds from neurobiology to nonlinear-dynamical circuits, to nonlinear neuro-controllers and to bio-inspired robots. It provides a concise exploration of t

"Covering a broad scope of modern nonlinear optics. Presenting both schemes of semiclassical theory of nonlinear susceptibility and quantum theory of radiation. Emphasizing equally the fundamental the

This book presents a modified model reference adaptive system (MRAS) observer for sensorless vector control of a wind driven doubly fed induction generator (DFIG). A mathematical model of the DFIG as

This book systematically presents the topological structure of solution sets and attractability for nonlinear evolution inclusions, together with its relevant applications in control problems and part

An expert in cell and developmental biology draws on the latest genetics research to present a new picture of evolution, with a testable, predictive model to explain the origin of species.

Taking a different approach from standard thousand-page reference-style control textbooks, Fundamentals of Linear Control provides a concise yet comprehensive introduction to the analysis and design of feedback control systems in fewer than 400 pages. The text focuses on classical methods for dynamic linear systems in the frequency domain. The treatment is, however, modern and the reader is kept aware of contemporary tools and techniques, such as state space methods and robust and nonlinear control. Featuring fully worked design examples, richly illustrated chapters, and an extensive set of homework problems and examples spanning across the text for gradual challenge and perspective, this textbook is an excellent choice for senior-level courses in systems and control or as a complementary reference in introductory graduate level courses. The text is designed to appeal to a broad audience of engineers and scientists interested in learning the main ideas behind feedback control theory.

This book introduces non-identifier-based adaptive control (with and without internal model) and its application to the current, speed and position control of mechatronic systems such as electrical sy

Introduction to Nonlinear Aeroelasticity Grigorios Dimitriadis, University of Liège, Belgium Introduces the latest developments and technologies in the area of nonlinear aeroelasticity Nonlinear a

Predictive Analytics For Dummies, 2e will?help the you understand the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data.?You will

The Mindful Legal Writer: Mastering Predictive and Persuasive Writing

Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for se

Linlin Li addresses the analysis and design issues of observer-based FD and FTC for nonlinear systems. The author analyses the existence conditions for the nonlinear observer-based FD systems to gain

Power System Stability: Modelling, Analysis and Control provides a comprehensive treatment of the subject from both a physical and mathematical perspective and covers a range of topics including model

"Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tip

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk a

Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical model

Every policy relies on explicit or implicit assumptions about how people make choices. Those assumptions typically rest on an idealized model of how people think, rather than an understanding of how e

Every policy relies on explicit or implicit assumptions about how people make choices. Those assumptions typically rest on an idealized model of how people think, rather than an understanding of how e

A discussion of challenges related to the modeling and control of greenhouse crop growth, this book presents state-of-the-art answers to those challenges. The authors model the subsystems involved in

This book provides an introduction to compositional semantics and to the syntax/semantics interface. It is rooted within the tradition of model theoretic semantics, and develops an explicit fragment o

Predictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques tha