Benchmark Models Of Control System Design For Remotely Operated Vehicles

This book is intended to meet the needs of those who seek to develop control systems for ROVs when there is no model available during the initial design stage. The modeling, simulation and application of marine vehicles like underwater robotic vehicles (URVs) are multidisciplinary, and combine mathematical aspects from various engineering disciplines. URVs such as remotely operated vehicle (ROVs) are used for a wide range of applications such as exploring the extreme depths of our ocean, where a hard-wired link is still required. Most ROVs operate in extreme environments with uncertainties in the model prior to control system design. However, the method involved extensive testing before the system model could be used for any control actions. It has been found that the range of error can be extensive and uncertain in actual, continuously varying conditions. Hence, it is important to address the problem of reliance on model testing using different modeling approaches. In this book, approaches such as WAMIT, ANSYS-CFX, STAR CCM+, MATLAB and Simulink are used to model parameters for ROVs. A few benchmark models are provided, allowing researchers and students to explore and test different control schemes. Given its scope, the book offers a valuable reference guide for postgraduate and undergraduate students engaged in modeling and simulation for ROV control.

Control systems are an integral aspect of modern society and exist across numerous domains and applications. As technology advances more and more, the complexity of such systems continues to increase exponentially. Model-Based Design for Effective Control System Development is a critical source of scholarly information on model-centric approaches and implementations for control and other similar dynamic systems. Highlighting innovative topics such as configuration management, controllability analysis, and modeling requirements, this book is ideally designed for engineers, researchers, academics, project managers, and professionals interested in the design of embedded control systems.

Control systems are pervasive in our lives. Our homes have environmental controls. The appliances we use at home, such as the washing machine, microwave, etc. have embedded controllers. We fly in airplanes and drive automobiles, which make extensive use of control systems. The increasing automation in the past few decades has increased our reliance on control systems.A First Course in Control System Design discusses control systems design from a model-based perspective as applicable to single-input single-output systems. The emphasis in this book is on understanding and applying the techniques that enable the design of effective control systems. The book covers the time-domain and the frequency-domain design methods, as well as the design of continuous-time and discrete-time systems.Technical topics discussed in the book include:  Modeling of physical systems Analysis of transfer function and state variable models Control system design via root locus  Control system design in the state-space Control design of sampled-data systems Compensator design via frequency response modification

Written to inspire and cultivate the ability to design and analyze feasible control algorithms for a wide range of engineering applications, this comprehensive text covers the theoretical and practical principles involved in the design and analysis of control systems. From the development of the mathematical models for dynamic systems, the author shows how they are used to obtain system response and facilitate control, then addresses advanced topics, such as digital control systems, adaptive and robust control, and nonlinear control systems.

This book features research papers presented at the 1st International Conference on Innovations in Data Analytics (ICIDA 2022), held at Eminent College of Management and Technology (ECMT), West Bengal, India, during November 29–30, 2022. The book presents original research work in the areas of computational intelligence, advance computing, network security and telecommunication, data science and data analytics, and pattern recognition. The book is beneficial for readers from both academia and industry.