Model Based Control

A highly accessible and unified approach to the design and analysis of intelligent control systems Adaptive Approximation Based Control is a tool every control designer should have in his or her control toolbox. Mixing approximation theory, parameter estimation, and feedback control, this book presents a unified approach designed to enable readers to apply adaptive approximation based control to existing systems, and, more importantly, to gain enough intuition and understanding to manipulate and combine it with other control tools for applications that have not been encountered before. The authors provide readers with a thought-provoking framework for rigorously considering such questions as: * What properties should the function approximator have? * Are certain families of approximators superior to others? * Can the stability and the convergence of the approximator parameters be guaranteed? * Can control systems be designed to be robust in the face of noise, disturbances, and unmodeled effects? * Can this approach handle significant changes in the dynamics due to such disruptions as system failure? * What types of nonlinear dynamic systems are amenable to this approach? * What are the limitations of adaptive approximation based control? Combining theoretical formulation and design techniques with extensive use of simulation examples, this book is a stimulating text for researchers and graduate students and a valuable resource for practicing engineers.

A unique treatment of signal processing using a model-based perspective Signal processing is primarily aimed at extracting useful information, while rejecting the extraneous from noisy data. If signal levels are high, then basic techniques can be applied. However, low signal levels require using the underlying physics to correct the problem causing these low levels and extracting the desired information. Model-based signal processing incorporates the physical phenomena, measurements, and noise in the form of mathematical models to solve this problem. Not only does the approach enable signal processors to work directly in terms of the problem's physics, instrumentation, and uncertainties, but it provides far superior performance over the standard techniques. Model-based signal processing is both a modeler's as well as a signal processor's tool. Model-Based Signal Processing develops the model-based approach in a unified manner and follows it through the text in the algorithms, examples, applications, and case studies. The approach, coupled with the hierarchy of physics-based models that the author develops, including linear as well as nonlinear representations, makes it a unique contribution to the field of signal processing. The text includes parametric (e.g., autoregressive or all-pole), sinusoidal, wave-based, and state-space models as some of the model sets with its focus on how they may be used to solve signal processing problems. Special features are provided that assist readers in understanding the material and learning how to apply their new knowledge to solving real-life problems. * Unified treatment of well-known signal processing models including physics-based model sets * Simple applications demonstrate how the model-based approach works, while detailed case studies demonstrate problem solutions in their entirety from concept to model development, through simulation, application to real data, and detailed performance analysis * Summaries provided with each chapter ensure that readers understand the key points needed to move forward in the text as well as MATLAB(r) Notes that describe the key commands and toolboxes readily available to perform the algorithms discussed * References lead to more in-depth coverage of specialized topics * Problem sets test readers' knowledge and help them put their new skills into practice The author demonstrates how the basic idea of model-based signal processing is a highly effective and natural way to solve both basic as well as complex processing problems. Designed as a graduate-level text, this book is also essential reading for practicing signal-processing professionals and scientists, who will find the variety of case studies to be invaluable. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department

This book is a contribution to the definition of a model based system engineering (MBSE) approach, designed to meet the objectives laid out by the INCOSE. After pointing out the complexity that jeopardizes a lot of system developments, the book examines fundamental aspects of systems under consideration. It goes on to address methodological issues and proposes a methodic approach of MBSE that provides, unlike current practices, systematic and integrated model-based engineering processes. An annex describes relevant features of the VHDL-AMS language supporting the methodological issues described in the book.

Presents modeling approaches that can be performed in SysML and other modeling languages This book combines the emerging discipline of systems architecting with model-based approaches using SysML. The early chapters of the book provide the fundamentals of systems architecting; discussing what systems architecting entails and how it benefits systems engineering. Model-based systems engineering is then defined, and its capabilities to develop complex systems on time and in a feasible quality are discussed. The remainder of the book covers important topics such as: architecture descriptions; architecture patterns; perspectives, viewpoints, views and their relation to system architecture; the roles of a system architect, their team, and stakeholders; systems architecting processes; agile approaches to systems architecting; variant modeling techniques; architecture frameworks; and architecture assessment. The book's organization allows experts to read the chapters out of sequence. Novices can read the chapters sequentially to gain a systematic introduction to system architecting. Model-Based System Architecture: Provides comprehensive coverage of the Functional Architecture for Systems (FAS) method created by the authors and based on common MBSE practices Covers architecture frameworks, including the System of Systems, Zachman Frameworks, TOGAF®, and more Includes a consistent example system, the “Virtual Museum Tour” system, that allows the authors to demonstrate the systems architecting concepts covered in the book Model-Based System Architecture is a comprehensive reference for system architects and systems engineers in technology companies. This book will also serve as a reference to students and researchers interested in functional architectures. Tim Weilkiens is the CEO at the German consultancy oose Innovative Informatik and co-author of the SysML specification. He has introduced model-based systems engineering to a variety of industry sectors. He is author of several books about modeling and the MBSE methodology SYSMOD. Jesko G. Lamm is a Senior Systems Engineer at Bernafon, a Swiss manufacturer for hearing instruments. With Tim Weilkiens, Jesko G. Lamm founded the Functional Architectures working group of the German chapter of INCOSE. Stephan Roth is a coach, consultant, and trainer for systems and software engineering at the German consultancy oose Innovative Informatik. He is a state-certified technical assistant for computer science from Physikalisch-Technische Lehranstalt (PTL) Wedel and a certified systems engineer (GfSE)®– Level C. Markus Walker works at Schindler Elevator in the research and development division as elevator system architect. He is an INCOSE Certified Systems Engineering Professional (CSEP) and is engaged in the committee of the Swiss chapter of INCOSE.

Provides a practical and comprehensive introduction to the key aspects of model-based testing as taught in the ISTQB® Model-Based Tester—Foundation Level Certification Syllabus This book covers the essentials of Model-Based Testing (MBT) needed to pass the ISTQB® Foundation Level Model-Based Tester Certification. The text begins with an introduction to MBT, covering both the benefits and the limitations of MBT. The authors review the various approaches to model-based testing, explaining the fundamental processes in MBT, the different modeling languages used, common good modeling practices, and the typical mistakes and pitfalls. The book explains the specifics of MBT test implementation, the dependencies on modeling and test generation activities, and the steps required to automate the generated test cases. The text discusses the introduction of MBT in a company, presenting metrics to measure success and good practices to apply. Provides case studies illustrating different approaches to Model-Based Testing Includes in-text exercises to encourage readers to practice modeling and test generation activities Contains appendices with solutions to the in-text exercises, a short quiz to test readers, along with additional information Model-Based Testing Essentials – Guide to the ISTQB® Certified Model-Based Tester – Foundation Level is written primarily for participants of the ISTQB® Certification: software engineers, test engineers, software developers, and anybody else involved in software quality assurance. This book can also be used for anyone who wants a deeper understanding of software testing and of the use of models for test generation.

Enables readers to master and apply the operator-theoretic approach Control of nonlinear systems is a multidisciplinary field involving electrical engineering, computer science, and control engineering. Specifically, this book addresses uncertain nonlinearity. Beginning with how real plants are modeled as operator-based plants, the author develops a systematic methodology that enables readers to understand a quantitative stability result, a critical factor in any nonlinear control system's stability and performance. Operator-Based Nonlinear Control Systems: Design and Applications focuses on the operator-theoretic approach, offering detailed examples on how to apply it to network controlled systems. In addition to current research results, the author explores future research directions and applications of the operator-theoretic approach. The book begins with an introduction that defines nonlinear systems. Next, it covers: Robust right coprime factorization for nonlinear plants with uncertainties Robust stability of operator-based nonlinear control systems Tracking issues and fault detection issues in nonlinear control systems Operator-based nonlinear control systems with smart actuators Nonlinear feedback control for large-scale systems using a distributed control system device Throughout the book, discussions of actual applications help readers understand how the operator-theoretic approach works in practice. Operator-Based Nonlinear Control Systems is recommended for students and professionals in control theory engineering and applied mathematics. Working with this expertly written and organized book, they will learn how to obtain robust right coprime factorization for modeled plants. Moreover, they will discover state-of-the-technology research results on robust stability conditions as well as the latest system output tracking and fault detection issues that are challenging today's researchers.

At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.

Explore the foundational and advanced subjects associated with proportional-integral-derivative controllers from leading authors in the field  In  PID Passivity-Based Control of Nonlinear Systems with Applications , expert researchers and authors Drs. Romeo Ortega, Jose Guadalupe Romero, Pablo Borja, and Alejandro Donaire deliver a comprehensive and detailed discussion of the most crucial and relevant concepts in the analysis and design of proportional-integral-derivative controllers using passivity techniques. The accomplished authors present a formal treatment of the recent research in the area and offer readers practical applications of the developed methods to physical systems, including electrical, mechanical, electromechanical, power electronics, and process control.  The book offers the material with minimal mathematical background, making it relevant to a wide audience. Familiarity with the theoretical tools reported in the control systems literature is not necessary to understand the concepts contained within. You’ll learn about a wide range of concepts, including disturbance rejection via PID control, PID control of mechanical systems, and Lyapunov stability of PID controllers.  Readers will also benefit from the inclusion of:  A thorough introduction to a class of physical systems described in the port-Hamiltonian form and a presentation of the systematic procedures to design PID-PBC for them An exploration of the applications to electrical, electromechanical, and process control systems of Lyapunov stability of PID controllers Practical discussions of the regulation and tracking of bilinear systems via PID control and their application to power electronics and thermal process control A concise treatment of the characterization of passive outputs, incremental models, and Port Hamiltonian and Euler-Lagrange systems Perfect for senior undergraduate and graduate students studying control systems,  PID Passivity-Based Control  will also earn a place in the libraries of engineers who practice in this area and seek a one-stop and fully updated reference on the subject.

Model Predictive Control of Wind Energy Conversion Systems addresses the predicative control strategy that has emerged as a promising digital control tool within the field of power electronics, variable-speed motor drives, and energy conversion systems. The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS. Furthermore, this book: Analyzes a wide variety of practical WECS, illustrating important concepts with case studies, simulations, and experimental results Provides a step-by-step design procedure for the development of predictive control schemes for various WECS configurations Describes continuous- and discrete-time modeling of wind generators and power converters, weighting factor selection, discretization methods, and extrapolation techniques Presents useful material for other power electronic applications such as variable-speed motor drives, power quality conditioners, electric vehicles, photovoltaic energy systems, distributed generation, and high-voltage direct current transmission. Explores S-Function Builder programming in MATLAB environment to implement various MPC strategies through the companion website Reflecting the latest technologies in the field, Model Predictive Control of Wind Energy Conversion Systems is a valuable reference for academic researchers, practicing engineers, and other professionals. It can also be used as a textbook for graduate-level and advanced undergraduate courses.