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Power System Fundamentals
Smart grids are linked with smart homes and smart meters. These smart grids are the new topology for generating, distributing, and consuming energy. If these smart devices are not connected in a smart grid, then they cannot work properly; hence, the conventional power systems are swiftly changing in order to improve the quality of electrical energy. This book covers the fundamentals of power systems—which are the pillars for smart grids —with a focus on defining the smart grid with theoretical and experimental electrical concepts. Power System Fundamentals begins by discussing electric circuits, the basic systems in smart grids, and finishes with a complete smart grid concept. The book allows the reader to build a foundation of understanding with basic and advanced exercises that run on simulation before moving to experimental results. It is intended for readers who want to comprehensively cover both the basic and advanced concepts of smart grids.
Real-time Iterative Learning Control
Real-time Iterative Learning Control demonstrates how the latest advances in iterative learning control (ILC) can be applied to a number of plants widely encountered in practice. The book gives a systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in linear and nonlinear plants pervading mechatronics and batch processes are addressed, in particular: ILC design in the continuous- and discrete-time domains; design in the frequency and time domains; design with problem-specific performance objectives including robustness and optimality; design in a modular approach by integration with other control techniques; and design by means of classical tools based on Bode plots and state space.
Stochastic Distribution Control System Design
A recent development in SDC-related problems is the establishment of intelligent SDC models and the intensive use of LMI-based convex optimization methods. Within this theoretical framework, control parameter determination can be designed and stability and robustness of closed-loop systems can be analyzed. This book describes the new framework of SDC system design and provides a comprehensive description of the modelling of controller design tools and their real-time implementation. It starts with a review of current research on SDC and moves on to some basic techniques for modelling and controller design of SDC systems. This is followed by a description of controller design for fixed-control-structure SDC systems, PDF control for general input- and output-represented systems, filtering designs, and fault detection and diagnosis (FDD) for SDC systems. Many new LMI techniques being developed for SDC systems are shown to have independent theoretical significance for robust control and FDD problems.
Model Predictive Control System Design and Implementation Using MATLAB®
Model Predictive Control System Design and Implementation Using MATLAB® proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters. After the theoretical presentation, coverage is given to three industrial applications. The subject of quadratic programming, often associated with the core optimization algorithms of MPC is also introduced and explained. The technical contents of this book is mainly based on advances in MPC using state-space models and basis functions. This volume includes numerous analytical examples and problems and MATLAB® programs and exercises.
Process Control
Passivity and associated stability conditions form one of the cornerstones in control theory and have begun to be applied in process control. In this book, passivity-based developments in all areas of control theory are addressed systematically for the first time. The emphasis is placed on real results that add insight. Case studies illustrate applications in all the main chapters. MATLAB® routines and a library of functions that implement the methods developed in the book can be downloaded from springer.com.
Control of Integral Processes with Dead Time
Control of Integral Processes with Dead Time provides a unified and coherent review of the various approaches devised for the control of integral processes, addressing the problem from different standpoints. In particular, the book treats the following topics: How to tune a PID controller and assess its performance; How to design a two-degree-of-freedom control scheme in order to deal with both the set-point following and load disturbance rejection tasks; How to modify the basic Smith predictor control scheme in order to cope with the presence of an integrator in the process; and how to address the presence of large process dead times. The methods are presented sequentially, highlighting the evolution of their rationale and implementation and thus clearly characterising them from both academic and industrial perspectives.
Practical PID Control
This book focuses on those functionalities that can provide significant improvements in Proportional–integral–derivative (PID) performance in combination with parameter tuning. In particular, the choice of filter to make the controller proper, the use of a feedforward action and the selection of an anti-windup strategy are addressed. The book gives the reader new methods for improving the performance of the most widely applied form of control in industry.
Industrial Process Identification and Control Design
Industrial Process Identification and Control Design is devoted to advanced identification and control methods for the operation of continuous-time processes both with and without time delay, in industrial and chemical engineering practice. The simple and practical step- or relay-feedback test is employed when applying the proposed identification techniques, which are classified in terms of common industrial process type: open-loop stable; integrating; and unstable, respectively. Correspondingly, control system design and tuning models that follow are presented for single-input-single-output processes. Furthermore, new two-degree-of-freedom control strategies and cascade control system desig...
Induction Motor Control Design
This book provides the most important steps and concerns in the design of estimation and control algorithms for induction motors. A single notation and modern nonlinear control terminology is used to make the book accessible, although a more theoretical control viewpoint is also given. Focusing on the induction motor with, the concepts of stability and nonlinear control theory given in appendices, this book covers: speed sensorless control; design of adaptive observers and parameter estimators; a discussion of nonlinear adaptive controls containing parameter estimation algorithms; and comparative simulations of different control algorithms. The book sets out basic assumptions, structural properties, modelling, state feedback control and estimation algorithms, then moves to more complex output feedback control algorithms, based on stator current measurements, and modelling for speed sensorless control. The induction motor exhibits many typical and unavoidable nonlinear features.
Optimal Control of Wind Energy Systems
Covering all aspects of this important topic, this work presents a review of the main control issues in wind power generation, offering a unified picture of the issues surrounding its optimal control. Discussion is focused on a global dynamic optimization approach to wind power systems using a set of optimization criteria which comply with a comprehensive group of requirements including: energy conversion efficiency; mechanical reliability; and quality of the energy provided.
