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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.
Assessment of Faults in Hybrid System Connected with Main Grid
Diversified Harmonics Modeling for Power System Stability Analysis
Comparative Study of Different Existing Standard Microgrid Networks
Application of Active Power Filter in the Hybrid Power System to Regulate the Grid Voltage
Dynamic Modeling of Drone Control with MatLAB Simulation
Development of New Bioinspired Hybrid Algorithms for Parameter Modeling of Photovoltaic Panels
Power Quality Improvement by Using PV-Integrated DSTATCOM
Modeling and Simulation of Current Transformer to Study Its Behaviors in Different Conditions
Multilevel Inverter-Fed Closed Loop Control and Analysis of Induction Motor Drive
Hybrid Grey Wolf Optimizer for Modeling and Control of Electric Drives
Parameter Estimation of First-Order RC Model of Lithium-Ion Batteries in Electric Vehicles Using Slime Mold Algorithm
Harmonic Distortion-Based Performance Analysis and Fault Diagnosis of Inverter Connected with BLDC Motor Using Starting Transients
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