Advanced System Modelling and Simulation with Block Diagram Languages explores and describes the use of block languages in dynamic modelling and simulation. The application of block diagrams to dynamic modelling is reviewed, not only in terms of known components and systems, but also in terms of the development of new systems. Methods by which block diagrams clarify the dynamic essence of systems and their components are emphasized throughout the book, and sufficient introductory material is included to elucidate the book's advanced material. Widely used continuous dynamic system simulation (CDSS) languages are analyzed, and their technical features are discussed. This self-contained resource includes a review section on block diagram algebra and applied transfer functions, both of which are important mathematical subjects, relevant to the understanding of continuous dynamic system simulation.

This book provides a tutorial in the use of Altair Compose and Altair Activate, software packages that provide system modeling and simulation facilities. Advanced system modeling software provide multiple ways of creating models: models can be programmed in specialized languages, graphically constructed as block-diagrams and state machines, or expressed mathematically in equation-based languages. Compose and Activate are introduced in this text in two parts. The first part introduces the multi-language environment of Compose and its use for modeling, simulation and optimization. The second describes the graphical system modeling and optimization with Activate, an open-system environment providing signal-based modeling as well as physical system component-based modeling. Throughout both parts are applied examples from mechanical, biological, and electrical systems, as well as control and signal processing systems. This book will be an invaluable addition with many examples both for those just interested in OML and those doing industrial scale modeling, simulation, and design. All examples are worked using the free basic editions of Activate and Compose that are available.

Designed as a text for undergraduate students (B.Tech./B.E.) of Computer Science and Engineering and IT, Mechanical Engineering and Mechatronics Engineering, and postgraduate students (M.Tech./M.E., M.Sc.) of Computer Science and Engineering and IT and Industrial Engineering, as well as for Bachelor and Master of Computer Applications (BCA/MCA), this well-organized book gives an in-depth analysis of the concepts of system simulation modelling and simulation languages. The book provides detailed discussions on the fundamental and advanced concepts of simulation. The book begins with the concept of system and the different terminologies associated with the system. Then it presents the different methods of random number generation and their tests. Besides, the text dwells on different probability distributions and their random variates, which are used in the simulation model, and describes various simulation languages such as GPSS, Simula I, SIMSCRIPT, CSL, GASP, OPS-3, DYNAMO, SIMAN and SLAM II. Further, it gives a comprehensive coverage of different queueing systems with illustrative examples as well as the logics of simulation model for both single-server and parallel-server queueing systems. The concluding chapters deal extensively with GPSS language, Arena simulation software and ProModel simulation software. Key Features • Follows a step-by-step approach to derive the test results. • Gives a large number of solved examples and well-designed chapter-end questions. • Includes several real-life Case Studies to illustrate the concepts discussed.

Modeling, Control And Optimization Of Complex Systems is a collection of contributions from leading international researchers in the fields of dynamic systems, control theory, and modeling. These papers were presented at the Symposium on Modeling and Optimization of Complex Systems in honor of Larry Yu-Chi Ho in June 2001. They include exciting research topics such as: -modeling of complex systems, -power control in ad hoc wireless networks, -adaptive control using multiple models, -constrained control, -linear quadratic control, -discrete events, -Markov decision processes and reinforcement learning, -optimal control for discrete event and hybrid systems, -optimal representation and visualization of multivariate data and functions in low-dimensional spaces.

A Practical Guide to SysML: The Systems Modeling Language is a comprehensive guide to SysML for systems and software engineers. It provides an advanced and practical resource for modeling systems with SysML. The source describes the modeling language and offers information about employing SysML in transitioning an organization or project to model-based systems engineering. The book also presents various examples to help readers understand the OMG Systems Modeling Professional (OCSMP) Certification Program. The text is organized into four parts. The first part provides an overview of systems engineering. It explains the model-based approach by comparing it with the document-based approach and providing the modeling principles. The overview of SYsML is also discussed. The second part of the book covers a comprehensive description of the language. It discusses the main concepts of model organization, parametrics, blocks, use cases, interactions, requirements, allocations, and profiles. The third part presents examples that illustrate how SysML supports different model-based procedures. The last part discusses how to transition and deploy SysML into an organization or project. It explains the integration of SysML into a systems development environment. Furthermore, it describes the category of data that are exchanged between a SysML tool and other types of tools, and the types of exchange mechanisms that can be used. It also covers the criteria that must be considered when selecting a SysML. Software and systems engineers, programmers, IT practitioners, experts, and non-experts will find this book useful.*The authoritative guide for understanding and applying SysML*Authored by the foremost experts on the language*Language description, examples, and quick reference guide included

A unique, hands-on guide to interactive modeling and simulation of engineering systems This book describes advanced, cutting-edge techniques for dynamic system simulation using the DESIRE modeling/simulation software package. It offers detailed guidance on how to implement the software, providing scientists and engineers with powerful tools for creating simulation scenarios and experiments for such dynamic systems as aerospace vehicles, control systems, or biological systems. Along with two new chapters on neural networks, Advanced Dynamic-System Simulation, Second Edition revamps and updates all the material, clarifying explanations and adding many new examples. A bundled CD contains an industrial-strength version of OPEN DESIRE as well as hundreds of program examples that readers can use in their own experiments. The only book on the market to demonstrate model replication and Monte Carlo simulation of real-world engineering systems, this volume: Presents a newly revised systematic procedure for difference-equation modeling Covers runtime vector compilation for fast model replication on a personal computer Discusses parameter-influence studies, introducing very fast vectorized statistics computation Highlights Monte Carlo studies of the effects of noise and manufacturing tolerances for control-system modeling Demonstrates fast, compact vector models of neural networks for control engineering Features vectorized programs for fuzzy-set controllers, partial differential equations, and agro-ecological modeling Advanced Dynamic-System Simulation, Second Edition is a truly useful resource for researchers and design engineers in control and aerospace engineering, ecology, and agricultural planning. It is also an excellent guide for students using DESIRE.

This book is a definitive introduction to models of computation for the design of complex, heterogeneous systems. It has a particular focus on cyber-physical systems, which integrate computing, networking, and physical dynamics. The book captures more than twenty years of experience in the Ptolemy Project at UC Berkeley, which pioneered many design, modeling, and simulation techniques that are now in widespread use. All of the methods covered in the book are realized in the open source Ptolemy II modeling framework and are available for experimentation through links provided in the book. The book is suitable for engineers, scientists, researchers, and managers who wish to understand the rich possibilities offered by modern modeling techniques. The goal of the book is to equip the reader with a breadth of experience that will help in understanding the role that such techniques can play in design.

Information Processing is a key area of research and development and the symposium presented state-of-the-art reports on some of the areas which are of relevance in automatic control: fault diagnosis and system reliability. Papers also covered the role of expert systems and other knowledge based systems, which are needed, to cope with the vast quantities of data generated by large scale systems. This volume should be considered essential reading for anyone involved in this rapidly developing area.

This introduction and textbook familiarizes engineers with the use of mathematical and computational modeling and simulation in a way that develops their understanding of the solution characteristics of a broad class of real-world problems. The relevant basic and advanced methodologies are explained in detail, with special emphasis on ill-defined problems. Some fifteen simulation systems are presented on the language and the logical level. Moreover, the reader also can accumulate an experiential overview by studying the wide variety of case studies spanning much of science and engineering. The latter are briefly described within the book but their full versions as well as some simulation software demos are available on the Web. The book can be used for courses on various levels as well as for self-study. Advanced sections are identified and can be skipped in a first reading or in undergraduate courses.

System Simulation Techniques with MATLAB and Simulink comprehensively explains how to use MATLAB and Simulink to perform dynamic systems simulation tasks for engineering and non-engineering applications. This book begins with covering the fundamentals of MATLAB programming and applications, and the solutions to different mathematical problems in simulation. The fundamentals of Simulink modelling and simulation are then presented, followed by coverage of intermediate level modelling skills and more advanced techniques in Simulink modelling and applications. Finally the modelling and simulation of engineering and non-engineering systems are presented. The areas covered include electrical, electronic systems, mechanical systems, pharmacokinetic systems, video and image processing systems and discrete event systems. Hardware-in-the-loop simulation and real-time application are also discussed. Key features: Progressive building of simulation skills using Simulink, from basics through to advanced levels, with illustrations and examples Wide coverage of simulation topics of applications from engineering to non-engineering systems Dedicated chapter on hardware-in-the-loop simulation and real time control End of chapter exercises A companion website hosting a solution manual and powerpoint slides System Simulation Techniques with MATLAB and Simulink is a suitable textbook for senior undergraduate/postgraduate courses covering modelling and simulation, and is also an ideal reference for researchers and practitioners in industry.