Linear and Nonlinear System Modelling

Written and edited by a team of experts in the field, this exciting new volume presents the cutting-edge techniques, latest trends, and state-of-the-art practical applications in linear and nonlinear system modeling. Mathematical modeling of control systems is, essentially, extracting the essence of practical problems into systematic mathematical language. In system modeling, mathematical expression deals with modeling and its applications. It is characterized that how a modeling competency can be categorized and its activity can contribute to building up these competencies. Mathematical modeling of a practical system is an attractive field of research and an advanced subject with a variety of applications. The main objective of mathematical modeling is to predict the behavior of the system under different operating conditions and to design and implement efficient control strategies to achieve the desired performance. A considerable effort has been directed to the development of models, which must be understandable and easy to analyze. It is a very difficult task to develop mathematical modeling of complicated practical systems considering all its possible high-level non-linearity and cross couple dynamics. Although mathematical modeling of nonlinear systems sounds quite interesting, it is difficult to formulate the general solution to analyze and synthesize nonlinear dynamical systems. Most of the natural processes are nonlinear, having very high computational complexity of several numerical issues. It is impossible to create any general solution or individual procedure to develop exact modeling of a non-linear system, which is often improper and too complex for engineering practices. Therefore, some series of approximation procedures are used, in order to get some necessary knowledge about the nonlinear system dynamics. There are several complicated mathematical approaches for solving these types of problems, such as functional analysis, differential geometry or the theory of nonlinear differential equations. Chapter 1 Assessment of Faults in Hybrid System Connected with Main Grid 1.1 Introduction 1.2 Hybrid System Connected with Main Grid 1.3 FFT Results in Different Conditions, Respective Bar Diagram, and Observations 1.4 Inter-Harmonic Group Analysis, Results, and Observations 1.5 Statistical Parameter Analysis Based on Discrete Wavelet Transform, Results, and Observations 1.6 Algorithm to Determine Non-Identical Conditions 1.7 Specific Outcome of This Chapter 1.8 Conclusions References Chapter 2 Diversified Harmonics Modeling for Power System Stability Analysis 2.1 Introduction 2.2 Classification 2.2.1 Steady-State Stability 2.2.2 Transient Stability 2.2.3 Dynamic Stability 2.3 Power Equation 2.4 Maximum Power 2.5 Nonlinearity and Harmonics 2.6 Active Power, Load Angle, and Reactance 2.7 Effects of Harmonics on Stability Model 2.7.1 Harmonic Reactance 2.7.2 Harmonic Power Equation and Harmonic Maximum Power 2.8 Harmonic Operating Point 2.8.1 Harmonic Power Versus Load Angle Characteristics 2.8.2 Harmonic Operating Point 2.8.3 Does HOP Hamper Overall Stability? 2.8.4 Importance of HOP 2.8.5 Steps for Determination of HOP 2.9 Case Studies 2.10 Conclusions References Chapter 3 Comparative Study of Different Existing Standard Microgrid Networks 3.1 Introduction 3.2 Classification of Microgrid Networks 3.2.1 DC Microgrid Network 3.2.2 AC Microgrid Network 3.2.3 Hybrid AC/DC Microgrid Network 3.3 Modes of Operation 3.4 General Equipment of a Microgrid Network 3.5 Basic Control Structure of Microgrid Network 3.6 Existing Standard Models 3.6.1 IEEE 14 Bus Microgrid Network 3.6.2 IEEE 9 Bus Microgrid Network 3.6.3 IEC 61850-7-420 Standard Microgrid Network 3.7 Considerations for Designing of Protection Schemes 3.8 Conclusion References Chapter 4 Application of Active Power Filter in the Hybrid Power System to Regulate the Grid Voltage 4.1 Introduction 4.2 System Topology Description 4.2.1 Solar Photovoltaic System 4.2.1.1 SPV Modeling 4.2.1.2 Maximum Power Point Tracking 4.2.1.3 Boost Converter 4.2.2 Wind Energy System 4.2.3 Modeling of Battery 4.2.4 Buck-Boost Converter 4.3 Series Active Power Filter Design 4.4 Simulation Results 4.4.1 Analysis Under Case 1 4.4.2 Analysis Under Case 2 4.5 Conclusion References Chapter 5 Dynamic Modeling of Drone Control with MATLAB Simulation 5.1 Introduction 5.2 Tool Description 5.3 Methodology 5.4 Overview of the Drone Control System 5.5 Overview of the Drone Control System in MATLAB Simulink 5.5.1 Flight Command 5.5.2 Flight Control System 5.5.3 Simulation Model 5.5.4 Flight Visualization 5.5.5 Result and Discussion 5.5.6 Varying the Values of Thrust Parameter of the Drone Flight Control 5.5.7 Varying the Values of Pitch Parameter of the Drone Flight Control 5.5.8 Varying the Values of Roll Parameter of the Drone Flight Control 5.5.9 Varying the Values of Yaw Parameter of the Drone Flight Control 5.5.10 Varying the Values of Thrust, Pitch, Roll, and Yaw Parameter of the Drone Flight Control 5.6 Applications 5.7 Conclusion References Chapter 6 Development of New Bioinspired Hybrid Algorithms for Parameter Modeling of Photovoltaic Panels 6.1 Introduction 6.2 Problem Statement 6.3 Proposed Bioinspired Techniques and Methodology 6.4 Simulation Results and Discussions 6.5 Conclusions References Chapter 7 Power Quality Improvement by Using PV-Integrated DSTATCOM 7.1 Introduction 7.2 Photovoltaic (PV)-Based DSTATCOM Model 7.3 Controller Design and Control Algorithm 7.3.1 Instantaneous Reactive Power Theory (IRPT) 7.3.2 Modified Instantaneous Reactive Power Theory (MIRPT) 7.3.3 Hybrid Synchronous Reference Frame Theory (HSRF) 7.3.4 Indirect Current Control (ICC) 7.3.5 Direct Current Control (DCC) 7.4 Simulation Results 7.5 Experimental Results 7.6 Conclusion References Chapter 8 Modeling and Simulation of Current Transformer to Study Its Behaviors in Different Conditions 8.1 Introduction 8.2 Simulation Circuit of Current Transformer 8.3 Effects of CT Performance Due to Variation of Circuit Time Constants 8.4 Effects of CT Performance Due to Switching Transients 8.5 DWT-Based Skewness Analysis for Assessment of CT Saturation Due to Switching Transients 8.6 CT Saturation Detection by Multi-Resolution Analysis- Based Notch Assessment 8.7 CT Primary Current Assessment During CT Saturation 8.8 Conclusion References Chapter 9 Multilevel Inverter-Fed Closed Loop Control and Analysis of Induction Motor Drive 9.1 Introduction 9.2 Mathematical Modeling 9.2.1 Field Weakening Controller 9.2.2 Vector Controller 9.3 Results 9.3.1 Starting Dynamics 9.3.2 Reversal Dynamics 9.3.3 Load Perturbation Analysis 9.3.4 THD Analysis 9.4 Conclusion References Chapter 10 Hybrid Grey Wolf Optimizer for Modeling and Control of Electric Drives 10.1 Background Study 10.2 Proposed Approach 10.3 Simulation Outcomes and Discussions 10.4 Conclusions References Chapter 11 Parameter Estimation of First-Order RC Model of Lithium-Ion Batteries in Electric Vehicles Using Slime Mold Algorithm 11.1 Introduction 11.2 Brief Overview of the Battery Models 11.2.1 Equivalent Circuit Model (ECM) of Li-Ion Battery 11.2.2 First-Order RC Equivalent Circuit Model 11.2.3 Fitness Function for Optimization 11.3 Slime Mold Algorithm (SMA) 11.4 Methodology 11.5 Simulation Results and Discussions 11.6 Conclusions References Chapter 12 Harmonic Distortion-Based Performance Analysis and Fault Diagnosis of Inverter Connected with BLDC Motor Using Starting Transients 12.1 Introduction 12.2 Modeling 12.3 THD Comparison of Phase Currents of Different Inverters 12.4 Variation of Harmonic Distortion of IGBT Inverter During Fault 12.5 Variation of Harmonic Distortion of MOSFET Inverter During Fault 12.6 Variation of Harmonic Distortion of Ideal Switch Inverter During Fault 12.7 Conclusion References About the Editors Index Also of Interest