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| robust control design with matlab code: Robust Control Design with MATLAB® Da-Wei Gu, Petko H. Petkov, Mihail M Konstantinov, 2006-03-30 Shows readers how to exploit the capabilities of the MATLAB® Robust Control and Control Systems Toolboxes to the fullest using practical robust control examples. |
| robust control design with matlab code: Design of Embedded Robust Control Systems Using MATLAB®/Simulink® Petko Hr. Petkov, Tsonyo N. Slavov, Jordan K. Kralev, 2018 The aim of this book is to give the necessary knowledge about the implementation of MATLABʼ and Simulinkʼ in the development of embedded control systems. Together, MATLAB and Simulink present a sophisticated programming environment which may be used for the design as well as for the implementation of embedded control systems. In this book, the authors exploit the opportunity to generate automatically and embed control code from Simulink models which allows to develop quickly efficient and error free code. The automated code generation and the availability of powerful processors make possible the implementation of complex high-order controllers which achieve fast and high-performance closed-loop dynamics. |
| robust control design with matlab code: Robust Control Design with MATLAB® Da-Wei Gu, Petko H. Petkov, Mihail M Konstantinov, 2014-07-08 Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: • rewritten and simplified presentation of theoretical and methodological material including original coverage of linear matrix inequalities; • new Part II forming a tutorial on Robust Control Toolbox 3; • fresh design problems including the control of a two-rotor dynamic system; and • end-of-chapter exercises. Electronic supplements to the written text that can be downloaded from extras.springer.com/isbn include: • M-files developed with MATLAB® help in understanding the essence of robust control system design portrayed in text-based examples; • MDL-files for simulation of open- and closed-loop systems in Simulink®; and • a solutions manual available free of charge to those adopting Robust Control Design with MATLAB® as a textbook for courses. Robust Control Design with MATLAB® is for graduate students and practising engineers who want to learn how to deal with robust control design problems without spending a lot of time in researching complex theoretical developments. |
| robust control design with matlab code: Linear Feedback Control Dingyu Xue, YangQuan Chen, Derek P. Atherton, 2007-01-01 Less mathematics and more working examples make this textbook suitable for almost any type of user. |
| robust control design with matlab code: Robust Control Andrzej Bartoszewicz, 2011-04-11 The main objective of this monograph is to present a broad range of well worked out, recent theoretical and application studies in the field of robust control system analysis and design. The contributions presented here include but are not limited to robust PID, H-infinity, sliding mode, fault tolerant, fuzzy and QFT based control systems. They advance the current progress in the field, and motivate and encourage new ideas and solutions in the robust control area. |
| robust control design with matlab code: Robust and Adaptive Control Eugene Lavretsky, Kevin A. Wise, 2025-02-22 Robust and Adaptive Control (second edition) shows readers how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications, the focus of the book is primarily on continuous-time dynamical systems. The two-part text begins with robust and optimal linear control methods and moves on to a self-contained presentation of the design and analysis of model reference adaptive control for nonlinear uncertain dynamical systems. Features of the second edition include: sufficient conditions for closed-loop stability under output feedback observer-based loop-transfer recovery (OBLTR) with adaptive augmentation; OBLTR applications to aerospace systems; case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; realistic examples and simulation data illustrating key featuresof the methods described; and problem solutions for instructors and MATLAB® code provided electronically. The theory and practical applications address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles drawn from the authors' extensive professional experience with The Boeing Company. The systems covered are challenging--often open-loop unstable with uncertainties in their dynamics--and thus require both persistently reliable control and the ability to track commands either from a pilot or a guidance computer. Readers should have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. The second edition contains a background summary of linear systems and control systems and an introduction to state observers and output feedback control, helping to make it self-contained. Robust and Adaptive Control teaches senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value. The solutions manual can be accessed by instructors who have adopted this book for their courses at https://sites.google.com/springernature.com/extramaterial/lecturer-material . To find the electronic supplementary material go to the publisher's website at https://link.springer.com/book/10.1007/978-3-031-38314-4. Please go to the Table of contents, to the chapter page linked through the title Introduction for ESM related to the chapters in Part I and to the chapter page linked through the title Direct Model Reference Adaptive Control: Motivation and Introduction for ESM related to Part II. The download link is in the column of links to the right of the page under the book cover thumbnail. |
| robust control design with matlab code: Robust Control Engineering Mario Garcia-Sanz, 2017-06-26 This book thoroughly covers the fundamentals of the QFT robust control, as well as practical control solutions, for unstable, time-delay, non-minimum phase or distributed parameter systems, plants with large model uncertainty, high-performance specifications, nonlinear components, multi-input multi-output characteristics or asymmetric topologies. The reader will discover practical applications through a collection of fifty successful, real world case studies and projects, in which the author has been involved during the last twenty-five years, including commercial wind turbines, wastewater treatment plants, power systems, satellites with flexible appendages, spacecraft, large radio telescopes, and industrial manufacturing systems. Furthermore, the book presents problems and projects with the popular QFT Control Toolbox (QFTCT) for MATLAB, which was developed by the author. |
| robust control design with matlab code: Fundamentals of Linear Control Maurício C. de Oliveira, 2017-05-04 Taking a different approach from standard thousand-page reference-style control textbooks, Fundamentals of Linear Control provides a concise yet comprehensive introduction to the analysis and design of feedback control systems in fewer than 400 pages. The text focuses on classical methods for dynamic linear systems in the frequency domain. The treatment is, however, modern and the reader is kept aware of contemporary tools and techniques, such as state space methods and robust and nonlinear control. Featuring fully worked design examples, richly illustrated chapters, and an extensive set of homework problems and examples spanning across the text for gradual challenge and perspective, this textbook is an excellent choice for senior-level courses in systems and control or as a complementary reference in introductory graduate level courses. The text is designed to appeal to a broad audience of engineers and scientists interested in learning the main ideas behind feedback control theory. |
| robust control design with matlab code: Modern Control Design Ashish Tewari, 2002-04-03 In this book, Tewari emphasizes the physical principles and engineering applications of modern control system design. Instead of detailing the mathematical theory, MATLAB examples are used throughout. |
| robust control design with matlab code: MATLAB Control Systems Engineering Cesar Lopez, 2014-09-22 MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Control Systems Engineering introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to design and analyze control systems using MATLAB’s specialized Control Systems Toolbox. The Control Systems Toolbox offers an extensive range of tools for classical and modern control design. Using these tools you can create models of linear time-invariant systems in transfer function, zero-pole-gain or state space format. You can manipulate both discrete-time and continuous-time systems and convert between various representations. You can calculate and graph time response, frequency response and loci of roots. Other functions allow you to perform pole placement, optimal control and estimates. The Control System Toolbox is open and extendible, allowing you to create customized M-files to suit your specific applications. |
| robust control design with matlab code: Robust Control Design with MATLAB Da-Wei Gu, Petko Hr. Petkov, Mihail M. Konstantinov, 2005 |
| robust control design with matlab code: Robust Control Farhad Assadian, Kevin R. Mallon, 2022-01-28 Robust Control Robust Control Youla Parameterization Approach Discover efficient methods for designing robust control systems In Robust Control: Youla Parameterization Approach, accomplished engineers Dr. Farhad Assadian and Kevin R. Mallon deliver an insightful treatment of robust control system design that does not require a theoretical background in controls. The authors connect classical control theory to modern control concepts using the Youla method and offer practical examples from the automotive industry for designing control systems with the Youla method. The book demonstrates that feedback control can be elegantly designed in the frequency domain using the Youla parameterization approach. It offers deep insights into the many practical applications from utilizing this technique in both Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) design. Finally, the book provides an estimation technique using Youla parameterization and controller output observer for the first time. Robust Control offers readers: A thorough introduction to a review of the Laplace Transform, including singularity functions and transfer functions Comprehensive explorations of the response of linear, time-invariant, and dynamic systems, as well as feedback principles and feedback design for SISO Practical discussions of norms and feedback systems, feedback design by the optimization of closed-loop norms, and estimation design for SISO using the parameterization approach In-depth examinations of MIMO control and multivariable transfer function properties Perfect for industrial researchers and engineers working with control systems, Robust Control: Youla Parameterization Approach is also an indispensable resource for graduate students in mechanical, aerospace, electrical, and chemical engineering. |
| robust control design with matlab code: Modeling, Analysis and Design of Control Systems in MATLAB and Simulink Dingyü Xue, YangQuan Chen, 2014-09 MATLAB and Simulink are now being used extensively in not only academia as a teaching aid, a learning aid and a research tool but also industry for modeling, analysis, design and rapid prototyping. As a response, Modeling, Analysis and Design of Control Systems in MATLAB and Simulink emphasizes on practical use of and problem solving in MATLAB and Simulink following the so-called MAD (modeling, analysis and design) notion. Readers can not only learn the control concepts and problem solving methods but also coding skills by following the numerous inline MATLAB scripts, functions, reproducible examples as well as chapter-end Problems. The book service website contains Solution Manual, 1, 000 plus teaching/learning PPTs, and all related codes used in the book for reproducing the examples.Modeling, Analysis and Design of Control Systems in MATLAB and Simulink has 12 chapters organized in 5 parts: Foundation, Modeling, Analysis, Design and Rapid Prototyping. Each chapter ends with Problems section. This book can be used as a reference text in the introductory control course for undergraduates in all engineering schools. The coverage of topics is broad, yet balanced, and it should provide a solid foundation for the subsequent control engineering practice in both industry and research institutes. This book will be a good desktop reference for control engineers and many codes and tools in this book may be directly applicable in real world problem solving. |
| robust control design with matlab code: Modern Control: State-Space Analysis and Design Methods Arie Nakhmani, 2020-05-01 Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Apply a state-space approach to modern control system analysis and design Written by an expert in the field, this concise textbook offers hands-on coverage of modern control system engineering. Modern Control: State-Space Analysis and Design Methods features start-to-finish design projects as well as online snippets of MATLAB code with simulations. The essential mathematics are presented along with fully worked-out examples in gradually increasing degrees of difficulty. Readers will receive “just-in-time” math background from a comprehensive appendix and get step-by-step descriptions of the latest analysis and design techniques. Coverage includes: • An introduction to control systems • State-space representations • Pole placement via state feedback • State estimators (observers) • Non-minimal canonical forms • Linearization • Lyapunov stability • Linear quadratic regulators (LQR) • Symmetric root locus (SRL) • Kalman filter • Linear quadratic gaussian control (LQG) |
| robust control design with matlab code: L1 Adaptive Control Theory Naira Hovakimyan, Chengyu Cao, 2010-09-30 Contains results not yet published in technical journals and conference proceedings. |
| robust control design with matlab code: Model Predictive Control System Design and Implementation Using MATLAB® Liuping Wang, 2009-02-14 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. |
| robust control design with matlab code: Feedback Systems Karl Johan Åström, Richard Murray, 2021-02-02 The essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory |
| robust control design with matlab code: Robust Control Engineering Mario Garcia-Sanz, 2017-06-26 This book thoroughly covers the fundamentals of the QFT robust control, as well as practical control solutions, for unstable, time-delay, non-minimum phase or distributed parameter systems, plants with large model uncertainty, high-performance specifications, nonlinear components, multi-input multi-output characteristics or asymmetric topologies. The reader will discover practical applications through a collection of fifty successful, real world case studies and projects, in which the author has been involved during the last twenty-five years, including commercial wind turbines, wastewater treatment plants, power systems, satellites with flexible appendages, spacecraft, large radio telescopes, and industrial manufacturing systems. Furthermore, the book presents problems and projects with the popular QFT Control Toolbox (QFTCT) for MATLAB, which was developed by the author. |
| robust control design with matlab code: MATLAB Programming for Biomedical Engineers and Scientists Andrew P. King, Paul Aljabar, 2017-06-14 MATLAB Programming for Biomedical Engineers and Scientists provides an easy-to-learn introduction to the fundamentals of computer programming in MATLAB. This book explains the principles of good programming practice, while demonstrating how to write efficient and robust code that analyzes and visualizes biomedical data. Aimed at the biomedical engineer, biomedical scientist, and medical researcher with little or no computer programming experience, it is an excellent resource for learning the principles and practice of computer programming using MATLAB. This book enables the reader to: - Analyze problems and apply structured design methods to produce elegant, efficient and well-structured program designs - Implement a structured program design in MATLAB, making good use of incremental development approaches - Write code that makes good use of MATLAB programming features, including control structures, functions and advanced data types - Write MATLAB code to read in medical data from files and write data to files - Write MATLAB code that is efficient and robust to errors in input data - Write MATLAB code to analyze and visualize medical data, including imaging data - Many real world biomedical problems and data show the practical application of programming concepts - Two whole chapters dedicated to the practicalities of designing and implementing more complex programs - An accompanying website containing freely available data and source code for the practical code examples, activities, and exercises in the book - For instructors, there are extra teaching materials including a complete set of slides, notes for a course based on the book, and course work suggestions |
| robust control design with matlab code: Practical Design and Application of Model Predictive Control Nassim Khaled, Bibin Pattel, 2018-05-04 Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB® and Simulink®. This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino®. The selected problems are nonlinear and challenging, and thus serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB® and Simulink® codes for the solutions are available for free download. Readers can connect with the authors through the dedicated website which includes additional free resources at www.practicalmpc.com. - Illustrates how to design, tune and deploy MPC for projects in a quick manner - Demonstrates a variety of applications that are solved using MATLAB® and Simulink® - Bridges the gap in providing a number of realistic problems with very hands-on training - Provides MATLAB® and Simulink® code solutions. This includes nonlinear plant models that the reader can use for other projects and research work - Presents application problems with solutions to help reinforce the information learned |
| robust control design with matlab code: Control Theory Tutorial Steven A. Frank, 2018-05-29 This open access Brief introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control. New students, as well as scientists from other backgrounds who want a concise and easy-to-grasp coverage of control theory, will benefit from the emphasis on concepts and broad understanding of the various approaches. Electronic codes for this title can be downloaded from https://extras.springer.com/?query=978-3-319-91707-8 |
| robust control design with matlab code: Robust Control of Robots Adriano A. G. Siqueira, Marco H. Terra, Marcel Bergerman, 2011-08-14 Robust Control of Robots bridges the gap between robust control theory and applications, with a special focus on robotic manipulators. It is divided into three parts: robust control of regular, fully-actuated robotic manipulators; robust post-failure control of robotic manipulators; and robust control of cooperative robotic manipulators. In each chapter the mathematical concepts are illustrated with experimental results obtained with a two-manipulator system. They are presented in enough detail to allow readers to implement the concepts in their own systems, or in Control Environment for Robots, a MATLAB®-based simulation program freely available from the authors. The target audience for Robust Control of Robots includes researchers, practicing engineers, and graduate students interested in implementing robust and fault tolerant control methodologies to robotic manipulators. |
| robust control design with matlab code: Extremum-Seeking Control and Applications Chunlei Zhang, Raúl Ordóñez, 2011-10-26 Extremum-seeking control tracks a varying maximum or minimum in a performance function such as output or cost. It attempts to determine the optimal performance of a control system as it operates, thereby reducing downtime and the need for system analysis. Extremum-seeking Control and Applications is divided into two parts. In the first, the authors review existing analog-optimization-based extremum-seeking control including gradient-, perturbation- and sliding-mode-based control designs. They then propose a novel numerical-optimization-based extremum-seeking control based on optimization algorithms and state regulation. This control design is developed for simple linear time-invariant systems and then extended for a class of feedback linearizable nonlinear systems. The two main optimization algorithms – line search and trust region methods – are analyzed for robustness. Finite-time and asymptotic state regulators are put forward for linear and nonlinear systems respectively. Further design flexibility is achieved using the robustness results of the optimization algorithms and the asymptotic state regulator by which existing nonlinear adaptive control techniques can be introduced for robust design. The approach used is easier to implement and tends to be more robust than those that use perturbation-based extremum-seeking control. The second part of the book deals with a variety of applications of extremum-seeking control: a comparative study of extremum-seeking control schemes in antilock braking system design; source seeking, formation control, collision and obstacle avoidance for groups of autonomous agents; mobile radar networks; and impedance matching. MATLAB®/Simulink® code which can be downloaded from www.springer.com/ISBN helps readers to reproduce the results presented in the text and gives them a head start for implementing the algorithms in their own applications. Extremum-seeking Control and Applications will interest academics and graduate students working in control, and industrial practitioners from a variety of backgrounds: systems, automotive, aerospace, communications, semiconductor and chemical engineering. |
| robust control design with matlab code: Control Engineering László Keviczky, Ruth Bars, Jenő Hetthéssy, Csilla Bányász, 2018-08-26 This book offers fundamental information on the analysis and synthesis of continuous and sampled data control systems. It includes all the required preliminary materials (from mathematics, signals and systems) that are needed in order to understand control theory, so readers do not have to turn to other textbooks. Sampled data systems have recently gained increasing importance, as they provide the basis for the analysis and design of computer-controlled systems. Though the book mainly focuses on linear systems, input/output approaches and state space descriptions are also provided. Control structures such as feedback, feed forward, internal model control, state feedback control, and the Youla parameterization approach are discussed, while a closing section outlines advanced areas of control theory. Though the book also contains selected examples, a related exercise book provides Matlab/Simulink exercises for all topics discussed in the textbook, helping readers to understand the theory and apply it in order to solve control problems. Thanks to this combination, readers will gain a basic grasp of systems and control, and be able to analyze and design continuous and discrete control systems. |
| robust control design with matlab code: Trends in Control Alberto Isidori, 2012-12-06 This book contains the text of the plenary lectures and the mini-courses of the European Control Conference (ECC 95) held in Rome, Italy, September 5-September 8, 1995. In particular, the book includes nine essays in which a selected number of prominent authorities present their views on some of the most recent developments in the theory and practice of control systems design and three self-contained sets of lecture notes. Some of the essays are focused on the topic of robust control. The article by J. Ackermann describes how to robustly control the rotational motions of a vehicle, to the purpose of simplifying the driver's task. The contribution by H. K wakernaak presents a detailed discussion of the requirements that performance and robustness impose on control systems design and of the symmetric roles of sensitivity and complementary sensitivity functions. The article by P. Boulet, B. A. Francis, P. C . Hughes and T. Hong describes an experimental testbed facility, called Daisy, whose dynamics emulate those of a real large flexible space structure and whose purpose is to test advanced identification and control design methods. The article of K. Glover discusses recent advances in uncertain system modeling, analysis and design, with ref erence to a flight control case study that has been test flown. The other essays describe advances in fundamental problems of control theory. The article by V. A. Yakubovich is a survey of certain new infinite horizon linear-quadratic optimization problems. The contribution by A. S. |
| robust control design with matlab code: Multivariable Feedback Control: Analysis and Design Sigurd Skogestad, 2014 |
| robust control design with matlab code: LMIs in Control Systems Guang-Ren Duan, Hai-Hua Yu, 2013-06-17 Although LMI has emerged as a powerful tool with applications across the major domains of systems and control, there has been a need for a textbook that provides an accessible introduction to LMIs in control systems analysis and design. Filling this need, LMIs in Control Systems: Analysis, Design and Applications focuses on the basic analysis and d |
| robust control design with matlab code: Linear Controller Design Stephen P. Boyd, Craig H. Barratt, 1991 |
| robust control design with matlab code: Model Predictive Control Basil Kouvaritakis, Mark Cannon, 2015-12-11 For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use of illustrative examples; sample problems; and discussion of novel control applications such as resource allocation for sustainable development and turbine-blade control for maximized power capture with simultaneously reduced risk of turbulence-induced damage. Graduate students pursuing courses in model predictive control or more generally in advanced or process control and senior undergraduates in need of a specialized treatment will find Model Predictive Control an invaluable guide to the state of the art in this important subject. For the instructor it provides an authoritative resource for the construction of courses. |
| robust control design with matlab code: Automatic Control of Atmospheric and Space Flight Vehicles Ashish Tewari, 2011-08-04 Automatic Control of Atmospheric and Space Flight Vehicles is perhaps the first book on the market to present a unified and straightforward study of the design and analysis of automatic control systems for both atmospheric and space flight vehicles. Covering basic control theory and design concepts, it is meant as a textbook for senior undergraduate and graduate students in modern courses on flight control systems. In addition to the basics of flight control, this book covers a number of upper-level topics and will therefore be of interest not only to advanced students, but also to researchers and practitioners in aeronautical engineering, applied mathematics, and systems/control theory. |
| robust control design with matlab code: Robust Python Patrick Viafore, 2021-07-12 Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Python is an easy language to learn and use, but that also means systems can quickly grow beyond comprehension. Thankfully, Python has features to help developers overcome maintainability woes. In this practical book, author Patrick Viafore shows you how to use Python's type system to the max. You'll look at user-defined types, such as classes and enums, and Python's type hinting system. You'll also learn how to make Python extensible and how to use a comprehensive testing strategy as a safety net. With these tips and techniques, you'll write clearer and more maintainable code. Learn why types are essential in modern development ecosystems Understand how type choices such as classes, dictionaries, and enums reflect specific intents Make Python extensible for the future without adding bloat Use popular Python tools to increase the safety and robustness of your codebase Evaluate current code to detect common maintainability gotchas Build a safety net around your codebase with linters and tests |
| robust control design with matlab code: Introduction to Control System Design (First Edition) Harry Kwatny, Bor-Chin Chang, 2020-05-27 Introduction to Control System Design equips students with the basic concepts, tools, and knowledge they need to effectively design automatic control systems. The text not only teaches readers how to design a control system, it inspires them to innovate and expand current methods to address new automation technology challenges and opportunities. The text is designed to support a two-quarter/semester course and is organized into two main parts. Part I covers basic linear system analysis and model-assembly concepts. It presents readers with a short history of control system design and introduces basic control concepts using first-order and second order-systems. Additional chapters address the modeling of mechanical and electrical systems, as well as assembling complex models using subsystem interconnection tools. Part II focuses on linear control system design. Students learn the fundamentals of feedback control systems; stability, regulation, and root locus design; time delay, plant uncertainty, and robust stability; and state feedback and linear quadratic optimization. The final chapter covers observer theory and output feedback control and reformulates the linear quadratic optimization problem as the more general H2 problem. |
| robust control design with matlab code: Advanced Sliding Mode Control for Mechanical Systems Jinkun Liu, Xinhua Wang, 2012-09-07 Advanced Sliding Mode Control for Mechanical Systems: Design, Analysis and MATLAB Simulation takes readers through the basic concepts, covering the most recent research in sliding mode control. The book is written from the perspective of practical engineering and examines numerous classical sliding mode controllers, including continuous time sliding mode control, discrete time sliding mode control, fuzzy sliding mode control, neural sliding mode control, backstepping sliding mode control, dynamic sliding mode control, sliding mode control based on observer, terminal sliding mode control, sliding mode control for robot manipulators, and sliding mode control for aircraft. This book is intended for engineers and researchers working in the field of control. Dr. Jinkun Liu works at Beijing University of Aeronautics and Astronautics and Dr. Xinhua Wang works at the National University of Singapore. |
| robust control design with matlab code: Modern Control Engineering Katsuhiko Ogata, 1990 Text for a first course in control systems, revised (1st ed. was 1970) to include new subjects such as the pole placement approach to the design of control systems, design of observers, and computer simulation of control systems. For senior engineering students. Annotation copyright Book News, Inc. |
| robust control design with matlab code: Learning for Adaptive and Reactive Robot Control Aude Billard, Sina Mirrazavi, Nadia Figueroa, 2022-02-08 Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions. |
| robust control design with matlab code: Robust Control in Power Systems Bikash Pal, Balarko Chaudhuri, 2006-07-02 Robust Control in Power Systems deals with the applications of new techniques in linear system theory to control low frequency oscillations in power systems. The book specifically focuses on the analysis and damping of inter-area oscillations in the systems which are in the range of 0.2-1 Hz. The damping control action is injected through high power electronic devices known as flexible AC transmission system (FACTS) controllers. Three commonly used FACTS controllers: controllable series capacitors (CSCs) controllable phase shifters (CPSs) and static var compensators (SVCs) have been used in this book to control the inter-area oscillations. The overview of linear system theory from the perspective of power system control is explained through examples. The damping control design is formulated as norm optimization problem. The H_infinity, H2 norm of properly defined transfer functions are minimized in linear matrix inequalities (LMI) framework to obtain desired performance and stability robustness. Both centralized and decentralized control structures are used. Usually the transmission of feedback signal from a remote location encounters delays making it difficult to control the system. Smith predictor based approach has been successfully explored in this book as a solution to such a problem. Robust Control in Power Systems will be valuable to academicians in the areas of power, control and system theory, as well as professionals in the power industry. |
| robust control design with matlab code: NASA Tech Briefs , 1995 |
ROBUST Definition & Meaning - Merriam-Webster
The meaning of ROBUST is having or exhibiting strength or vigorous health. How to use robust in a sentence. Synonym Discussion of Robust.
ROBUST | English meaning - Cambridge Dictionary
ROBUST definition: 1. (of a person or animal) strong and healthy, or (of an object or system) strong and unlikely to…. Learn more.
ROBUST Definition & Meaning | Dictionary.com
Robust definition: strong and healthy; hardy; vigorous.. See examples of ROBUST used in a sentence.
Robust - definition of robust by The Free Dictionary
Powerfully built; sturdy: a robust body. 3. Requiring or characterized by much strength or energy: a robust workout. 4. a. Active or dynamic: a robust debate; a robust economy. b. Working in an …
robust adjective - Definition, pictures, pronunciation and usage …
Definition of robust adjective from the Oxford Advanced Learner's Dictionary. strong and healthy. She was almost 90, but still very robust. He seems to be in robust (good) health. Want to learn …
ROBUST definition and meaning | Collins English Dictionary
Someone or something that is robust is very strong or healthy. More women than men go to the doctor. Perhaps men are more robust or worry less? We've always specialised in making very …
What does robust mean? - Definitions.net
Robust generally refers to the strength, health, or ability of something to withstand adverse conditions or rough handling. In a broader context, it can also refer to the capacity of a system …
Robust - Definition, Meaning & Synonyms - Vocabulary.com
Use robust to describe a person or thing that is healthy and strong, or strongly built. This adjective also commonly describes food or drink: a robust wine has a rich, strong flavor.
ROBUST Synonyms: 194 Similar and Opposite Words - Merriam-Webster
Synonyms for ROBUST: healthy, sturdy, well, strong, whole, wholesome, fit, hale; Antonyms of ROBUST: weak, feeble, sick, unhealthy, unfit, ill, unsound, diseased
Meaning of robust – Learner’s Dictionary - Cambridge Dictionary
ROBUST definition: strong and healthy: . Learn more.
ROBUST Definition & Meaning - Merriam-Webster
The meaning of ROBUST is having or exhibiting strength or vigorous health. How to use robust in a sentence. Synonym Discussion of Robust.
ROBUST | English meaning - Cambridge Dictionary
ROBUST definition: 1. (of a person or animal) strong and healthy, or (of an object or system) strong and unlikely to…. Learn more.
ROBUST Definition & Meaning | Dictionary.com
Robust definition: strong and healthy; hardy; vigorous.. See examples of ROBUST used in a sentence.
Robust - definition of robust by The Free Dictionary
Powerfully built; sturdy: a robust body. 3. Requiring or characterized by much strength or energy: a robust workout. 4. a. Active or dynamic: a robust debate; a robust economy. b. Working in an effective way; effective or …
robust adjective - Definition, pictures, pronunciation and usag…
Definition of robust adjective from the Oxford Advanced Learner's Dictionary. strong and healthy. She was almost 90, but still very robust. He seems to be in robust (good) health. Want to learn more? strong; able to …
