Data-Driven, Nonparametric, Adaptive Control Theory introduces a novel approach to the control of deterministic, nonlinear ordinary differential equations affected by uncertainties.
Data-Driven, Nonparametric, Adaptive Control Theory introduces a novel approach to the control of deterministic, nonlinear ordinary differential equations affected by uncertainties.
Control Systems Benchmarks helps control engineers, researchers, and students to evaluate and compare control system performance across a range of critical applications by offering a collection of real-world benchmarks.
This book constitutes the referred proceedings of the 7th International Conference on Attacks and Defenses for Internet-of-Things, ADIoT 2024, held as an hybrid event, in Hangzhou, China, during December 13–14, 2024.
This book presents selected, peer-reviewed contributions from the International Symposium on Mathematical Analysis of Fractals and Dynamical Systems-2023 (ISMAFDS - 2023), held at the Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Tamil Nadu in India during August 24-25, 2023.
This book develops a coherent and quite general theoretical approach to algorithm design for iterative learning control based on the use of operator representations and quadratic optimization concepts including the related ideas of inverse model control and gradient-based design.
This comprehensive textbook presents a self-contained guide to bioinformatics, defined in its broadest sense as the application of information science to biology.
Structured Controllers for Uncertain Systems focuses on the development of easy-to-use design strategies for robust low-order or fixed-structure controllers (particularly the industrially ubiquitous PID controller).
Stock Market Modeling and Forecasting translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics.
Finite-time stability (FTS) is a more practical concept than classical Lyapunov stability, useful for checking whether the state trajectories of a system remain within pre-specified bounds over a finite time interval.
This second edition of the popular textbook contains a comprehensive course in modern probability theory, covering a wide variety of topics which are not usually found in introductory textbooks, including: * limit theorems for sums of random variables* martingales* percolation* Markov chains and electrical networks* construction of stochastic processes* Poisson point process and infinite divisibility* large deviation principles and statistical physics* Brownian motion* stochastic integral and stochastic differential equations.
This book shows how the use of S-variables (SVs) in enhancing the range of problems that can be addressed with the already-versatile linear matrix inequality (LMI) approach to control can, in many cases, be put on a more unified, methodical footing.
The subject of this brief is the application of linear parameter-varying (LPV) control to a class of dynamic systems to provide a systematic synthesis of gain-scheduling controllers with guaranteed stability and performance.
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.
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.
Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events.
Control of Discrete-event Systems provides a survey of the most important topics in the discrete-event systems theory with particular focus on finite-state automata, Petri nets and max-plus algebra.
Frequency Domain Criteria for Absolute Stability focuses on recently-developed methods of delay-integral-quadratic constraints to provide criteria for absolute stability of nonlinear control systems.
Stochastic Averaging and Extremum Seeking treats methods inspired by attempts to understand the seemingly non-mathematical question of bacterial chemotaxis and their application in other environments.
The intention of this book is not to add another technical work to the series of publications already available on matters connected with the relations between natural and artificial intelligence, nor to repeat the positions already well expressed in, for example, the debate between John Searle, Daniel Dennet and Hubert Dreyfus.
Problems, methods and algorithms of decision making based on an uncertain knowledge now create a large and intensively developing area in the field of knowledge-based decision support systems.
Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type: How does a machine learn a concept on the basis of examples?
H-infinity control theory deals with the minimization of the H-infinity-norm of the transfer matrix from an exogenous disturbance to a pertinent controlled output of a given plant.
This work is aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control sys- tems, signal processing, and linear algebra.
Mobile Robotics: A Practical Introduction is an excellent introduction to the foundations and methods used for designing completely autonomous mobile robots.
This book has evolved from our combined experience of working in computing services at the University of London (for the last nine years at King's College, and before that eight years at Imperial College and seven at Chelsea College) in the teaching, advice and technical support of Fortran and related areas.
Search and Classification Using Multiple Autonomous Vehicles provides a comprehensive study of decision-making strategies for domain search and object classification using multiple autonomous vehicles (MAV) under both deterministic and probabilistic frameworks.
0 e This is the proceedings of the first annual symposium of the Safety-critical Systems Club (The Watershed Media Centre, Bristol, 9-11 February 1993), which provided a forum for exploring and discussing ways of achieving safety in computer systems to be used in safety-critical industrial applications.
Neural Network Applications contains the 12 papers presented at the second British Neural Network Society Meeting (NCM '91) held at King's College London on 1st October 1991.
