Systems engineering encompasses a variety of components that embrace physical and conceptual phenomena. This book addresses all aspects of systems modeling and simulation. The first part of the text presents a step-by-step procedure for modeling different types of systems using techniques like a graph theoretic approach, interpretive structural modeling, and system dynamics modeling. It also covers physical systems framework and identification, systems analysis, and optimization aspects and numerical analysis. The second part presents real-life examples of simulation that illustrate state-of-the-art simulation. The text also develops MATLAB(R) and Simulink programs for system simulation.
Devendra K. Chaturvedi (Dayalbagh Educational Institute India)
CRC Press Inc
Country of Publication:
16 December 2009
Introduction to Systems System Classification of Systems Linear Systems Time-Varying vs. Time-Invariant Systems Lumped vs. Distributed Parameter Systems Continuous- and Discrete-Time Systems Deterministic vs. Stochastic Systems Hard and Soft Systems Analysis of Systems Synthesis of Systems Introduction to System Philosophy System Thinking Large and Complex Applied System Engineering: A Generic Modeling Systems Modeling Introduction Need of System Modeling Modeling Methods for Complex Systems Classification of Models Characteristics of Models Modeling Mathematical Modeling of Physical Systems Formulation of State Space Model of Systems Physical Systems Theory System Components and Interconnections Computation of Parameters of a Component Single Port and Multiport Systems Techniques of System Analysis Basics of Linear Graph Theoretic Approach Formulation of System Model for Conceptual System Formulation System Model for Physical Systems Topological Restrictions Development of State Model of Degenerative System Solution of State Equations Controllability Observability Sensitivity Liapunov Stability Performance Characteristics of Linear Time Invariant Systems Formulation of State Space Model Using Computer Program (SYSMO) Model Order Reduction Introduction Difference between Model Simplification and Model Order Reduction Need for Model Order Reduction Principle of Model Order Reduction Methods of Model Order Reduction Applications of Reduced-Order Models Analogous of Linear Systems Introduction Force-Voltage (f-v) Analogy Force-Current (f-i) Analogy Interpretive Structural Modeling Introduction Graph Theory Interpretive Structural Modeling System Dynamics Techniques Introduction System Dynamics of Managerial and Socioeconomic System Traditional Management Sources of Information Strength of System Dynamics Experimental Approach to System Analysis System Dynamics Technique Structure of a System Dynamic Model Basic Structure of System Dynamics Models Different Types of Equations Used in System Dynamics Techniques Symbol Used in Flow Diagrams Dynamo Equations Modeling and Simulation of Parachute Deceleration Device Modeling of Heat Generated in a Parachute during Deployment Modeling of Stanchion System of Aircraft Arrester Barrier System Simulation Introduction Advantages of Simulation When to Use Simulations Simulation Provides How Simulations Improve Analysis and Decision Making Applications of Simulation Numerical Methods for Simulation The Characteristics of Numerical Methods Comparison of Different Numerical Methods Errors during Simulation with Numerical Methods Nonlinear and Chaotic Systems Introduction Linear vs. Nonlinear System Types of Nonlinearities Nonlinearities in Flight Control of Aircraft Conclusions Introduction to Chaotic System Historical Prospective First-Order Continuous-Time System Bifurcations Second-Order System Third-Order System Modeling with Artificial Neural Network Introduction Artificial Neural Networks Modeling Using Fuzzy Systems Introduction Fuzzy Sets Features of Fuzzy Sets Operations on Fuzzy Sets Characteristics of Fuzzy Sets Properties of Fuzzy Sets Fuzzy Cartesian Product Fuzzy Relation Approximate Reasoning Defuzzification Methods Introduction to Fuzzy Rule-Based Systems Applications of Fuzzy Systems to System Modeling Takagi-Sugeno-Kang Fuzzy Models Adaptive Neuro-Fuzzy Inferencing Systems Steady State DC Machine Model Transient Model of a DC Machine Fuzzy System Applications for Operations Research Discrete-Event Modeling and Simulation Introduction Some Important Definitions Queuing System Discrete-Event System Simulation Components of Discrete-Event System Simulation Input Data Modeling Family of Distributions for Input Data Random Number Generation Chi-Square Test Kolomogrov-Smirnov Test Appendix A: MATLAB Appendix B: Simulink Appendix C: Glossary Index
Devendra K. Chaturvedi is a professor in the Department of Electrical Engineering at Dayalbagh Educational Institute in India.