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Attractive Ellipsoids in Robust Control
This monograph introduces a newly developed robust-control design technique for a wide class of continuous-time dynamical systems called the “attractive ellipsoid method.” Along with a coherent introduction to the proposed control design and related topics, the monograph studies nonlinear affine control systems in the presence of uncertainty and presents a constructive and easily implementable control strategy that guarantees certain stability properties. The authors discuss linear-style feedback control synthesis in the context of the above-mentioned systems. The development and physical implementation of high-performance robust-feedback controllers that work in the absence of complete information is addressed, with numerous examples to illustrate how to apply the attractive ellipsoid method to mechanical and electromechanical systems. While theorems are proved systematically, the emphasis is on understanding and applying the theory to real-world situations. Attractive Ellipsoids in Robust Control will appeal to undergraduate and graduate students with a background in modern systems theory as well as researchers in the fields of control engineering and applied mathematics.
Chaos Synchronization and Cryptography for Secure Communications: Applications for Encryption
Over the past few decades, there has been numerous research studies conducted involving the synchronization of dynamical systems with several theoretical studies and laboratory experimentations demonstrating the pivotal role for this phenomenon in secure communications. Chaos Synchronization and Cryptography for Secure Communications: Applications for Encryption explores the combination of ordinary and time delayed systems and their applications in cryptographic encoding. This innovative publication presents a critical mass of the most sought after research, providing relevant theoretical frameworks and the latest empirical research findings in this area of study.
Differential Neural Networks For Robust Nonlinear Control: Identification, State Estimation And Trajectory Tracking
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.).
Systems Structure and Control
The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc.
Robust Control
This "Robust Control" course consists of 25 lectures aimed at graduate students in Electrical and Mechanical Engineering. It focuses on how modern robust control theory addresses real-world problems. Robustness is defined by three requirements: the plant model may be inexact or uncertain, the system must handle external perturbations, and the controller should be simple for easy implementation. The course is divided into five parts: Mathematical Background and Linear Matrix Inequalities in Control Theory, Absolute Stability and H1-Control, Attractive Ellipsoid Method (AEM), Sliding Mode Control (SMC), and Engineering Examples. Topics include conditions for LMI solutions, Schur’s lemma extension, dynamic feedback controller design using AEM, robust control for time-delay systems, Sampled-Data and Quantized Output systems, SMC methods, and Absolute Stability analysis. This course complements existing resources and provides practical tools for feedback design.
Industrial and Robotic Systems
This volume gathers the latest advances, innovations, and applications in the field of robotics engineering, as presented by leading international researchers and engineers at the Latin American Symposium on Industrial and Robotic Systems (LASIRS), held in Tampico, Mexico on October-November 30-01 2019. The contributions cover all major areas of R&D and innovation in simulation, optimization, and control of robotics, such as design and optimization of robots using numerical and metaheuristic methods, autonomous and control systems, industrial compliance solutions, numerical simulations for manipulators and robots, metaheuristics applied to robotics problems, Industry 4.0, control and automation in petrochemical processes, simulation and control in aerospace and aeronautics, and education in robotics. The conference represented a unique platform to share the latest research and developments in simulation, control and optimization of robotic systems, and to promote cooperation among specialists in machine and mechanism area.
Advances in Neural Networks – ISNN 2019
This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.
Classical and Analytical Mechanics
Classical and Analytical Mechanics: Theory, Applied Examples, and Practice provides a bridge between the theory and practice related to mechanical, electrical, and electromechanical systems. It includes rigorous mathematical and physical explanations while maintaining an interdisciplinary engineering focus. Applied problems and exercises in mechanical, mechatronic, aerospace, electrical, and control engineering are included throughout and the book provides detailed techniques for designing models of different robotic, electrical, defense, and aerospace systems. The book starts with multiple chapters covering kinematics before moving onto coverage of dynamics and non-inertial and variable mas...
