-PDF Download- Controller Tuning Optimization Methods For Multi Constraints And Nonlinear Systems EBOOK

Controller Tuning Optimization Methods for Multi-Constraints and Nonlinear Systems

Author: Maude Josée Blondin

Publisher: Springer Nature

Published: 2021-01-06

Total Pages: 107

ISBN-13: 303064541X

This book covers controller tuning techniques from conventional to new optimization methods for diverse control engineering applications. Classical controller tuning approaches are presented with real-world challenges faced in control engineering. Current developments in applying optimization techniques to controller tuning are explained. Case studies of optimization algorithms applied to controller tuning dealing with nonlinearities and limitations like the inverted pendulum and the automatic voltage regulator are presented with performance comparisons. Students and researchers in engineering and optimization interested in optimization methods for controller tuning will utilize this book to apply optimization algorithms to controller tuning, to choose the most suitable optimization algorithm for a specific application, and to develop new optimization techniques for controller tuning.

Deep Learning Technologies for the Sustainable Development Goals

Author: Virender Kadyan

Publisher: Springer Nature

Published: 2023-02-01

Total Pages: 254

ISBN-13: 9811957231

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This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.

Industrial PID Controller Tuning

Author: José David Rojas

Publisher:

Published: 2021

Total Pages: 0

ISBN-13: 9783030723125

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Industrial PID Controller Tuning presents a different view of the servo/regulator compromise that has been studied for a long time in industrial control research. Optimal tuning generally involves comparison of cost functions (e.g., a quadratic function of the error or a time-weighted absolute value of the error) but without taking advantage of available multi-objective optimization methods. The book does make use of multi-objective optimization to account for several sources of disturbance, applying them to a more realistic problem: how to select the tuning of a controller when both servo and regulator responses are important. The authors review the different deterministic multi-objective optimization methods. In order to ameliorate the consequences of the computational expense typically involved in their use-specifically the generation of multiple solutions among which the control engineer still has to choose-algorithms for two-degree-of-freedom PID control are implemented in MATLAB®. MATLAB code and a MATLAB-compatible program are provided for download and will help readers to adapt the ideas presented in the text for use in their own systems. Further practical guidance is offered by the inclusion of several examples of common industrial processes amenable to the use of the authors' methods. Researchers interested in non-heuristic approaches to controller tuning or in decision-making after a Pareto set has been established and graduate students interested in beginning a career working with PID control and/or industrial controller tuning will find this book a valuable reference and source of ideas. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

PID Control

Author: Tamer Mansour

Publisher: BoD – Books on Demand

Published: 2011-04-19

Total Pages: 250

ISBN-13: 9533071664

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The PID controller is considered the most widely used controller. It has numerous applications varying from industrial to home appliances. This book is an outcome of contributions and inspirations from many researchers in the field of PID control. The book consists of two parts; the first is related to the implementation of PID control in various applications whilst the second part concentrates on the tuning of PID control to get best performance. We hope that this book can be a valuable aid for new research in the field of PID control in addition to stimulating the research in the area of PID control toward better utilization in our life.

Control of Nonlinear and Hybrid Process Systems

Author: Panagiotis D. Christofides

Publisher: Springer Science & Business Media

Published: 2005-10-04

Total Pages: 736

ISBN-13: 9783540284567

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This monograph provides insight and fundamental understanding into the feedback control of nonlinear and hybrid process systems. It presents state-of-the-art methods for the synthesis of nonlinear feedback controllers for nonlinear and hybrid systems with uncertainty, constraints and time-delays with numerous applications, especially to chemical processes. It covers both state feedback and output feedback (including state estimator design) controller designs. Control of Nonlinear and Hybrid Process Systems includes numerous comments and remarks providing insight and fundamental understanding into the feedback control of nonlinear and hybrid systems, as well as applications that demonstrate the implementation and effectiveness of the presented control methods. The book includes many detailed examples which can be easily modified by a control engineer to be tailored to a specific application. This book is useful for researchers in control systems theory, graduate students pursuing their degree in control systems and control engineers.

Multi-Objective Optimization System Designs and Their Applications

Author: Bor-Sen Chen

Publisher: CRC Press

Published: 2023-12-05

Total Pages: 292

ISBN-13: 1000999521

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This book introduces multi-objective design methods to solve multi-objective optimization problems (MOPs) of linear/nonlinear dynamic systems under intrinsic random fluctuation and external disturbance. The MOPs of multiple targets for systems are all transformed into equivalent linear matrix inequality (LMI)-constrained MOPs. Corresponding reverse-order LMI-constrained multi-objective evolution algorithms are introduced to solve LMI-constrained MOPs using MATLAB®. All proposed design methods are based on rigorous theoretical results, and their applications are focused on more practical engineering design examples. Features: Discusses multi-objective optimization from an engineer’s perspective. Contains the theoretical design methods of multi-objective optimization schemes. Includes a wide spectrum of recent research topics in control design, especially for stochastic mean field diffusion problems. Covers practical applications in each chapter, like missile guidance design, economic and financial systems, power control tracking, minimization design in communication, and so forth. Explores practical multi-objective optimization design examples in control, signal processing, communication, and cyber-financial systems. This book is aimed at researchers and graduate students in electrical engineering, control design, and optimization.

PID Controller Design Approaches

Author: Marialena Vagia

Publisher: BoD – Books on Demand

Published: 2012-03-28

Total Pages: 302

ISBN-13: 9535104055

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First placed on the market in 1939, the design of PID controllers remains a challenging area that requires new approaches to solving PID tuning problems while capturing the effects of noise and process variations. The augmented complexity of modern applications concerning areas like automotive applications, microsystems technology, pneumatic mechanisms, dc motors, industry processes, require controllers that incorporate into their design important characteristics of the systems. These characteristics include but are not limited to: model uncertainties, system's nonlinearities, time delays, disturbance rejection requirements and performance criteria. The scope of this book is to propose different PID controllers designs for numerous modern technology applications in order to cover the needs of an audience including researchers, scholars and professionals who are interested in advances in PID controllers and related topics.

Controller Tuning with Evolutionary Multiobjective Optimization

Author: Gilberto Reynoso Meza

Publisher: Springer

Published: 2018-06-23

Total Pages: 0

ISBN-13: 9783319823171

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This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO). It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.

Computational Intelligence and Optimization Methods for Control Engineering

Author: Maude Josée Blondin

Publisher: Springer Nature

Published: 2019-09-20

Total Pages: 355

ISBN-13: 3030254461

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This volume presents some recent and principal developments related to computational intelligence and optimization methods in control. Theoretical aspects and practical applications of control engineering are covered by 14 self-contained contributions. Additional gems include the discussion of future directions and research perspectives designed to add to the reader’s understanding of both the challenges faced in control engineering and the insights into the developing of new techniques. With the knowledge obtained, readers are encouraged to determine the appropriate control method for specific applications.

Hybrid Predictive Control for Dynamic Transport Problems

Author: Alfredo Nunez

Publisher: Springer Science & Business Media

Published: 2012-10-03

Total Pages: 183

ISBN-13: 1447143515

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Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: · hybrid predictive control (HPC) design based on evolutionary multiobjective optimization (EMO); · HPC based on EMO for dial-a-ride systems; and · HPC based on EMO for operational decisions in public transport systems. Hybrid Predictive Control for Dynamic Transport Problems is a comprehensive analysis of HPC and its application to dynamic transport systems. Introductory material on evolutionary algorithms is presented in summary in an appendix. The text will be of interest to control and transport engineers working on the operational optimization of transport systems and to academic researchers working with hybrid systems. The potential applications of the generic methods presented here to other process fields will make the book of interest to a wider group of researchers, scientists and graduate students working in other control-related disciplines.