The simulation of complex, integrated engineering systems is a core tool in industry which has been greatly enhanced by the MATLAB® and Simulink® software programs. The second edition of Dynamic Systems: Modeling, Simulation, and Control teaches engineering students how to leverage powerful simulation environments to analyze complex systems. Designed for introductory courses in dynamic systems and control, this textbook emphasizes practical applications through numerous case studies—derived from top-level engineering from the AMSE Journal of Dynamic Systems. Comprehensive yet concise chapters introduce fundamental concepts while demonstrating physical engineering applications. Aligning with current industry practice, the text covers essential topics such as analysis, design, and control of physical engineering systems, often composed of interacting mechanical, electrical, and fluid subsystem components. Major topics include mathematical modeling, system-response analysis, and feedback control systems. A wide variety of end-of-chapter problems—including conceptual problems, MATLAB® problems, and Engineering Application problems—help students understand and perform numerical simulations for integrated systems.

This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.

Continuous-system simulation is an increasingly important tool for optimizing the performance of real-world systems. The book presents an integrated treatment of continuous simulation with all the background and essential prerequisites in one setting. It features updated chapters and two new sections on Black Swan and the Stochastic Information Packet (SIP) and Stochastic Library Units with Relationships Preserved (SLURP) Standard. The new edition includes basic concepts, mathematical tools, and the common principles of various simulation models for different phenomena, as well as an abundance of case studies, real-world examples, homework problems, and equations to develop a practical understanding of concepts.

This tutorial provides a variety of simulation algorithms for the design and control of dynamic systems. It explains the accuracy and stability of automatic control theory, emphasizing those systems described by stiff non-linear differential equations.

Craig Kluever ‘s Dynamic Systems: Modeling, Simulation, and Control highlights essential topics such as analysis, design, and control of physical engineering systems, often composed of interacting mechanical, electrical and fluid subsystem components. The major topics covered in this text include mathematical modeling, system-response analysis, and an introduction to feedback control systems. Dynamic Systems integrates an early introduction to numerical simulation using MATLAB®’s Simulink for integrated systems. Simulink® and MATLAB® tutorials for both software programs will also be provided. The author’s text also has a strong emphasis on real-world case studies.

Learn the latest techniques in programming sophisticated simulation systems This cutting-edge text presents the latest techniques in advanced simulation programming for interactive modeling and simulation of dynamic systems, such as aerospace vehicles, control systems, and biological systems. The author, a leading authority in the field, demonstrates computer software that can handle large simulation studies on standard personal computers. Readers can run, edit, and modify the sample simulations from the text with the accompanying CD-ROM, featuring the OPEN DESIRE program for Linux and Windows. The program included on CD solves up to 40,000 ordinary differential equations and implements exceptionally fast and convenient vector operations. The text begins with an introduction to dynamic-system simulation, including a demonstration of a simple guided-missile simulation. Among the other highlights of coverage are: Models that involve sampled-data operations and sampled-data difference equations, including improved techniques for proper numerical integration of switched variables Novel vector compiler that produces exceptionally fast programs for vector and matrix assignments, differential equations, and difference equations Application of vector compiler to parameter-influence studies and Monte Carlo simulation of dynamic systems Vectorized Monte Carlo simulations involving time-varying noise, derived from periodic pseudorandom-noise samples Vector models of neural networks, including a new pulsed-neuron model Vectorized programs for fuzzy-set controller, partial differential equations, and agro-ecological models replicated at many points of a landscape map This text is intended for graduate-level students, engineers, and computer scientists, particularly those involved in aerospace, control system design, chemical process control, and biological systems. All readers will gain the practical skills they need to design sophisticated simulations of dynamic systems. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Showing you how to use personal computers for modeling and simulation, Interactive Dynamic-System Simulation, Second Edition provides a practical tutorial on interactive dynamic-system modeling and simulation. It discusses how to effectively simulate dynamical systems, such as aerospace vehicles, power plants, chemical processes, control systems, a