Nonlinear Control of Engineering Systems

Author: Warren E. Dixon
Publisher: Springer Science & Business Media
ISBN: 1461200318
Format: PDF, Docs
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This practical yet rigorous book provides a development of nonlinear, Lyapunov-based tools and their use in the solution of control-theoretic problems. Rich in motivating examples and new design techniques, the text balances theoretical foundations and real-world implementation.

Nonlinear Dynamical Systems and Control

Author: Wassim M. Haddad
Publisher: Princeton University Press
ISBN: 1400841046
Format: PDF, Mobi
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Nonlinear Dynamical Systems and Control presents and develops an extensive treatment of stability analysis and control design of nonlinear dynamical systems, with an emphasis on Lyapunov-based methods. Dynamical system theory lies at the heart of mathematical sciences and engineering. The application of dynamical systems has crossed interdisciplinary boundaries from chemistry to biochemistry to chemical kinetics, from medicine to biology to population genetics, from economics to sociology to psychology, and from physics to mechanics to engineering. The increasingly complex nature of engineering systems requiring feedback control to obtain a desired system behavior also gives rise to dynamical systems. Wassim Haddad and VijaySekhar Chellaboina provide an exhaustive treatment of nonlinear systems theory and control using the highest standards of exposition and rigor. This graduate-level textbook goes well beyond standard treatments by developing Lyapunov stability theory, partial stability, boundedness, input-to-state stability, input-output stability, finite-time stability, semistability, stability of sets and periodic orbits, and stability theorems via vector Lyapunov functions. A complete and thorough treatment of dissipativity theory, absolute stability theory, stability of feedback systems, optimal control, disturbance rejection control, and robust control for nonlinear dynamical systems is also given. This book is an indispensable resource for applied mathematicians, dynamical systems theorists, control theorists, and engineers.

Nonlinear Systems Stability Analysis

Author: Seyed Kamaleddin Yadavar Nikravesh
Publisher: CRC Press
ISBN: 1466569298
Format: PDF, Docs
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The equations used to describe dynamic properties of physical systems are often nonlinear, and it is rarely possible to find their solutions. Although numerical solutions are impractical and graphical techniques are not useful for many types of systems, there are different theorems and methods that are useful regarding qualitative properties of nonlinear systems and their solutions—system stability being the most crucial property. Without stability, a system will not have value. Nonlinear Systems Stability Analysis: Lyapunov-Based Approach introduces advanced tools for stability analysis of nonlinear systems. It presents the most recent progress in stability analysis and provides a complete review of the dynamic systems stability analysis methods using Lyapunov approaches. The author discusses standard stability techniques, highlighting their shortcomings, and also describes recent developments in stability analysis that can improve applicability of the standard methods. The text covers mostly new topics such as stability of homogonous nonlinear systems and higher order Lyapunov functions derivatives for stability analysis. It also addresses special classes of nonlinear systems including time-delayed and fuzzy systems. Presenting new methods, this book provides a nearly complete set of methods for constructing Lyapunov functions in both autonomous and nonautonomous systems, touching on new topics that open up novel research possibilities. Gathering a body of research into one volume, this text offers information to help engineers design stable systems using practice-oriented methods and can be used for graduate courses in a range of engineering disciplines.

Reinforcement Learning for Optimal Feedback Control

Author: Rushikesh Kamalapurkar
Publisher: Springer
ISBN: 331978384X
Format: PDF, Docs
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Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements. This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.

Nonlinear and Adaptive Control with Applications

Author: Alessandro Astolfi
Publisher: Springer Science & Business Media
ISBN: 9781848000667
Format: PDF, ePub, Docs
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The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.

Nonlinear Control of Wheeled Mobile Robots

Author: Warren E. Dixon
Publisher: Springer Verlag
ISBN:
Format: PDF, Mobi
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This book examines the control problem for wheeled mobile robots. Several novel control strategies are developed and the stability of each controller is examined utilizing Lyapunov techniques. The performance of each controller is either illustrated through simulation results or experimental results. The final chapter describes how the control techniques developed for wheeled mobile robots can be applied to solve other problems with similar governing differential equations (e.g., twin rotor helicopters, surface vessels). Several appendices are included to provide the reader with the mathematical background utilized in the control development and stability analysis. Two appendices are also included that provide specific details with regard to the modifications that were done to commercially available mobile robots (e.g., a K2A manufactured by Cybermotion Inc. and a Pioneer II manufactured by Activemedia) to experimentally demonstrate the performance of the torque input controllers.

Analysis and Synthesis of Fuzzy Control Systems

Author: Gang Feng
Publisher: CRC Press
ISBN: 9781420092653
Format: PDF
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Fuzzy logic control (FLC) has proven to be a popular control methodology for many complex systems in industry, and is often used with great success as an alternative to conventional control techniques. However, because it is fundamentally model free, conventional FLC suffers from a lack of tools for systematic stability analysis and controller design. To address this problem, many model-based fuzzy control approaches have been developed, with the fuzzy dynamic model or the Takagi and Sugeno (T–S) fuzzy model-based approaches receiving the greatest attention. Analysis and Synthesis of Fuzzy Control Systems: A Model-Based Approach offers a unique reference devoted to the systematic analysis and synthesis of model-based fuzzy control systems. After giving a brief review of the varieties of FLC, including the T–S fuzzy model-based control, it fully explains the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy systems. This enables the book to be self-contained and provides a basis for later chapters, which cover: T–S fuzzy modeling and identification via nonlinear models or data Stability analysis of T–S fuzzy systems Stabilization controller synthesis as well as robust H∞ and observer and output feedback controller synthesis Robust controller synthesis of uncertain T–S fuzzy systems Time-delay T–S fuzzy systems Fuzzy model predictive control Robust fuzzy filtering Adaptive control of T–S fuzzy systems A reference for scientists and engineers in systems and control, the book also serves the needs of graduate students exploring fuzzy logic control. It readily demonstrates that conventional control technology and fuzzy logic control can be elegantly combined and further developed so that disadvantages of conventional FLC can be avoided and the horizon of conventional control technology greatly extended. Many chapters feature application simulation examples and practical numerical examples based on MATLAB®.

Nonlinear and Optimal Control Systems

Author: Thomas L. Vincent
Publisher: John Wiley & Sons
ISBN: 9780471042358
Format: PDF, Kindle
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Nonlinear dynamical systems; Nonlinear control systems; Nonlinear optimization; Lyapunov stability; Lyapunov control systems design; Optimal control systems; Optimal control design; Differential games; References; Index.

Constructive Nonlinear Control

Author: R. Sepulchre
Publisher: Springer Science & Business Media
ISBN: 1447109678
Format: PDF, ePub, Mobi
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Constructive Nonlinear Control presents a broad repertoire of constructive nonlinear designs not available in other works by widening the class of systems and design tools. Several streams of nonlinear control theory are merged and directed towards a constructive solution of the feedback stabilization problem. Analysis, geometric and asymptotic concepts are assembled as design tools for a wide variety of nonlinear phenomena and structures. Geometry serves as a guide for the construction of design procedures whilst analysis provides the robustness which geometry lacks. New recursive designs remove earlier restrictions on feedback passivation. Recursive Lyapunov designs for feedback, feedforward and interlaced structures result in feedback systems with optimality properties and stability margins. The design-oriented approach will make this work a valuable tool for all those who have an interest in control theory.

Robust Control of Nonlinear Uncertain Systems

Author: Zhihua Qu
Publisher: John Wiley & Sons
ISBN: 9780471115892
Format: PDF
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The first comprehensive, self-contained text on nonlinear analysis and robust control Increasingly, robust control plays a greater role in achieving high performance for systems that are too complex to be modeled accurately. Using Lyapunov's direct method to develop design procedures, compare different controls, and give the reader a definite feel for stability analysis and robust control for nonlinear systems with significant uncertainty, this unique text: * Presents the complete set of robust control design procedures for nonlinear uncertain systems * Introduces the recursive interlacing design method that will generate robust control for uncertain systems with cascaded, feedback, and feedforward dynamics * Covers a broad range of robust control designs, including state feedback and input-output, continuous-time and digital, and static and dynamic controls * Gives advice on selecting design parameters according to their impact on stability and performance * Features illustrations as well as end-of-chapter exercises and references