Engineering Systems and Sustainability – serie

Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation.In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research.This modest volume is intended to be a useful addition to the literature on identifying CT systems.

This book intends to be a comprehensive text on the topic of integrated circuits for power management, putting together both theoretical foundations and practical details, leading to successful design practices in research and industry. It covers all the three main categories of power management circuits, viz., linear regulators, inductor-based switchers and switched-capacitor circuits, and presents detailed discussion of their common topologies, operation and modeling.FeaturesIncludes underlying theory and design/implementation practical ingredients for power management integrated circuits (PMICs).Provides in-depth analysis of topologies and circuits related to linear regulators, switched-capacitor converters and inductor-based converters.Covers all the relevant topics at the intersection between power electronics and integrated circuit design areas.Provides guidelines for design of circuits and solutions for all the pertinent topologies.Indicates all important issues and the related trade-offs in the design of PMICs.The book will be a valuable resource for senior- and graduate-level students as well as industry professionals who have done university-level courses on analog circuit design, control systems and power electronics.

Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for stochastic systems with traditional and emerging engineering-oriented complexities. The book begins with an overview of the relevant background, motivation, and research problems, and then:Discusses the robust stability and stabilization problems for a class of stochastic time-delay interval systems with nonlinear disturbancesInvestigates the robust stabilization and H∞ control problems for a class of stochastic time-delay uncertain systems with Markovian switching and nonlinear disturbancesExplores the H∞ state estimator and H∞ output feedback controller design issues for stochastic time-delay systems with nonlinear disturbances, sensor nonlinearities, and Markovian jumping parametersAnalyzes the H∞ performance for a general class of nonlinear stochastic systems with time delays, where the addressed systems are described by general stochastic functional differential equationsStudies the filtering problem for a class of discrete-time stochastic nonlinear time-delay systems with missing measurement and stochastic disturbancesUses gain-scheduling techniques to tackle the probability-dependent control and filtering problems for time-varying nonlinear systems with incomplete informationEvaluates the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with multiple random communication delays and random packet lossesExamines the filtering problem for a class of nonlinear genetic regulatory networks with state-dependent stochastic disturbances and state delaysConsiders the H∞ state estimation problem for a class of discrete-time complex networks with probabilistic missing measurements and randomly occurring coupling delaysAddresses the H∞ synchronization control problem for a class of dynamical networks with randomly varying nonlinearitiesNonlinear Stochastic Control and Filtering with Engineering-oriented Complexities describes novel methodologies that can be applied extensively in lab simulations, field experiments, and real-world engineering practices. Thus, this text provides a valuable reference for researchers and professionals in the signal processing and control engineering communities.

Explore a Viable Resource for DesalinationThe world’s freshwater supplies are rapidly depleting and seawater is being positioned as a major feasible replacement in the search for a sustainable water source. Focused on large-scale multi-stage flash (MSF) seawater desalination plants, and based on research conducted on a real 18-stage plant, Multi-Stage Flash Desalination: Modeling, Simulation and Adaptive Control outlines the principles and processes of MSF desalination and highlights the state of the art in MSF desalination modeling, simulation, and control. This book offers a brief overview of MSF plants, explains the importance of the various control systems for large MSF plants, and describes methods of mathematical modeling centered on physical phenomena in the MSF process. It introduces a developed dynamic model and illustrates the simulation of the model using an equation-based flowsheet simulation package (SPEEDUP) from AspenTech. It also presents a method for finding and using a non-parametric model in designing optimal PID control systems and recommends an adaptive scheme that maintains optimal plant operation over a range of operating conditions. The improvements suggested by the author for PID controllers are pervasive in desalination plants of high dimension and also relate to other process industries with comparable conditions. He also discusses the use of renewable energy sources for desalination and stresses the potential of solar energy in the Arab region, an area known for its aridity and scarcity of water.The text: Details the dynamic model of the various elements in an MSF plantConsiders the obtained model as well as available measurement dataPresents a developed model for use in PID controlProvides descriptions, listings, and additional reference material for further research Multi-Stage Flash Desalination: Modeling, Simulation and Adaptive Control covers the processes of desalination and the operation and control of MSF plants for large-scale desalination and provides you with a greater understanding of dynamics, operation, and control.

Explore a Viable Resource for DesalinationThe world’s freshwater supplies are rapidly depleting and seawater is being positioned as a major feasible replacement in the search for a sustainable water source. Focused on large-scale multi-stage flash (MSF) seawater desalination plants, and based on research conducted on a real 18-stage plant, Multi-Stage Flash Desalination: Modeling, Simulation and Adaptive Control outlines the principles and processes of MSF desalination and highlights the state of the art in MSF desalination modeling, simulation, and control. This book offers a brief overview of MSF plants, explains the importance of the various control systems for large MSF plants, and describes methods of mathematical modeling centered on physical phenomena in the MSF process. It introduces a developed dynamic model and illustrates the simulation of the model using an equation-based flowsheet simulation package (SPEEDUP) from AspenTech. It also presents a method for finding and using a non-parametric model in designing optimal PID control systems and recommends an adaptive scheme that maintains optimal plant operation over a range of operating conditions. The improvements suggested by the author for PID controllers are pervasive in desalination plants of high dimension and also relate to other process industries with comparable conditions. He also discusses the use of renewable energy sources for desalination and stresses the potential of solar energy in the Arab region, an area known for its aridity and scarcity of water.The text: Details the dynamic model of the various elements in an MSF plantConsiders the obtained model as well as available measurement dataPresents a developed model for use in PID controlProvides descriptions, listings, and additional reference material for further researchMulti-Stage Flash Desalination: Modeling, Simulation and Adaptive Control covers the processes of desalination and the operation and control of MSF plants for large-scale desalination and provides you with a greater understanding of dynamics, operation, and control.