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| Author | : Oscar Castillo |
| Publisher | : |
| Total Pages | : 184 |
| Release | : 2005 |
| Genre | : |
| ISBN | : |
| Author | : Oscar Castillo |
| Publisher | : Physica |
| Total Pages | : 231 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3790818321 |
This book presents a unified view of modelling, simulation, and control of non linear dynamical systems using soft computing techniques and fractal theory. Our particular point of view is that modelling, simulation, and control are problems that cannot be considered apart, because they are intrinsically related in real world applications. Control of non-linear dynamical systems cannot be achieved if we don't have the appropriate model for the system. On the other hand, we know that complex non-linear dynamical systems can exhibit a wide range of dynamic behaviors ( ranging from simple periodic orbits to chaotic strange attractors), so the problem of simulation and behavior identification is a very important one. Also, we want to automate each of these tasks because in this way it is more easy to solve a particular problem. A real world problem may require that we use modelling, simulation, and control, to achieve the desired level of performance needed for the particular application.
| Author | : Patricia Melin |
| Publisher | : Harwood Academic Publishers |
| Total Pages | : 272 |
| Release | : 2001-01-01 |
| Genre | : |
| ISBN | : 9789056992750 |
| Author | : Jan Awrejcewicz |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 336 |
| Release | : 2008-12-26 |
| Genre | : Technology & Engineering |
| ISBN | : 1402087780 |
This volume contains the invited papers presented at the 9th International Conference "Dynamical Systems — Theory and Applications" held in Lódz, Poland, December 17-20, 2007, dealing with nonlinear dynamical systems. The conference brought together a large group of outstanding scientists and engineers, who deal with various problems of dynamics encountered both in engineering and in daily life. Topics covered include, among others, bifurcations and chaos in mechanical systems; control in dynamical systems; asymptotic methods in nonlinear dynamics; stability of dynamical systems; lumped and continuous systems vibrations; original numerical methods of vibration analysis; and man-machine interactions. Thus, the reader is given an overview of the most recent developments of dynamical systems and can follow the newest trends in this field of science. This book will be of interest to to pure and applied scientists working in the field of nonlinear dynamics.
| Author | : Mahmoud ElHefnawi |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 306 |
| Release | : 2012-03-30 |
| Genre | : Computers |
| ISBN | : 9535104098 |
New applications in recurrent neural networks are covered by this book, which will be required reading in the field. Methodological tools covered include ranking indices for fuzzy numbers, a neuro-fuzzy digital filter and mapping graphs of parallel programmes. The scope of the techniques profiled in real-world applications is evident from chapters on the recognition of severe weather patterns, adult and foetal ECGs in healthcare and the prediction of temperature time-series signals. Additional topics in this vein are the application of AI techniques to electromagnetic interference problems, bioprocess identification and I-term control and the use of BRNN-SVM to improve protein-domain prediction accuracy. Recurrent neural networks can also be used in virtual reality and nonlinear dynamical systems, as shown by two chapters.
| Author | : Yuri Tiumentsev |
| Publisher | : Academic Press |
| Total Pages | : 332 |
| Release | : 2019-05-17 |
| Genre | : Science |
| ISBN | : 0128154306 |
Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft. Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and training Offers application examples of dynamic neural network technologies, primarily related to aircraft Provides an overview of recent achievements and future needs in this area
| Author | : Abdelhamid Mellouk |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 486 |
| Release | : 2011-01-14 |
| Genre | : Computers |
| ISBN | : 9533073691 |
Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic.
| Author | : Abdul Kareem |
| Publisher | : LAP Lambert Academic Publishing |
| Total Pages | : 124 |
| Release | : 2012-04 |
| Genre | : |
| ISBN | : 9783659109171 |
Most physical plants are nonlinear in nature and coupled with uncertain dynamics due to external disturbances or unmodeled nonlinearities or even unpredictable faults. In many cases, a good response of complex and highly nonlinear real process is difficult to obtain by applying conventional techniques based on linear mathematical models of the process. The performance of the conventional controller deteriorates as the operating point changes. Also, non-linear dynamical systems are difficult to control due to the unstable and even chaotic behaviors and uncertainties that may occur in these systems. In the present industrial scenario, it is required to have automatic control with good performance over a wide operating range with simple design and implementation. The application of Soft Computing techniques is a good alternative for controlling non-linear dynamical systems with uncertainties in real-world problems. This book deals with Soft Computing based algorithms for the control of dynamic uncertain systems. In this book, the design of algorithms with DC-DC Converter as an example are discussed. Also, the simulations based on Matlab/Simulink are presented.
| Author | : Azar, Ahmad Taher |
| Publisher | : IGI Global |
| Total Pages | : 706 |
| Release | : 2018-02-09 |
| Genre | : Computers |
| ISBN | : 1522540784 |
Complex systems are pervasive in many areas of science. With the increasing requirement for high levels of system performance, complex systems has become an important area of research due to its role in many industries. Advances in System Dynamics and Control provides emerging research on the applications in the field of control and analysis for complex systems, with a special emphasis on how to solve various control design and observer design problems, nonlinear systems, interconnected systems, and singular systems. Featuring coverage on a broad range of topics, such as adaptive control, artificial neural network, and synchronization, this book is an important resource for engineers, professionals, and researchers interested in applying new computational and mathematical tools for solving the complicated problems of mathematical modeling, simulation, and control.
| Author | : Adrian Olaru |
| Publisher | : Mdpi AG |
| Total Pages | : 0 |
| Release | : 2023-03-31 |
| Genre | : |
| ISBN | : 9783036571041 |
This book contains all the articles published in the Special Issue "Dynamic Modeling and Simulation for Control Systems" from the MDPI Mathematics journal. This Special Issue aims to cover important aspects of how to optimize the dynamic behavior of physical systems using special algorithms and artificial intelligence in the modeling, simulation, and optimization of components and systems from important fields such as astronautics, aerospace, avionics, robotics, manufacturing systems, mechanical engineering, power energy, materials technology, and neurorehabilitation. It is our hope that this Special Issue will contribute to the research on techniques for the modeling, simulation, and optimization of control systems in dynamic systems.
