System Identification For Adaptive Nonlinear Flight Control Using Neural Networks
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| Author | : Yiannis Boutalis |
| Publisher | : Springer Science & Business |
| Total Pages | : 316 |
| Release | : 2014-04-23 |
| Genre | : Technology & Engineering |
| ISBN | : 3319063642 |
Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
| Author | : N. Sundararajan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 167 |
| Release | : 2013-03-09 |
| Genre | : Science |
| ISBN | : 1475752865 |
Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.
| Author | : Oliver Nelles |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 785 |
| Release | : 2013-03-09 |
| Genre | : Technology & Engineering |
| ISBN | : 3662043238 |
Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
| Author | : |
| Publisher | : |
| Total Pages | : 124 |
| Release | : 1995 |
| Genre | : Airplanes |
| ISBN | : |
| Author | : Jay A. Farrell |
| Publisher | : John Wiley & Sons |
| Total Pages | : 440 |
| Release | : 2006-04-14 |
| Genre | : Science |
| ISBN | : 0471781800 |
A highly accessible and unified approach to the design and analysis of intelligent control systems Adaptive Approximation Based Control is a tool every control designer should have in his or her control toolbox. Mixing approximation theory, parameter estimation, and feedback control, this book presents a unified approach designed to enable readers to apply adaptive approximation based control to existing systems, and, more importantly, to gain enough intuition and understanding to manipulate and combine it with other control tools for applications that have not been encountered before. The authors provide readers with a thought-provoking framework for rigorously considering such questions as: * What properties should the function approximator have? * Are certain families of approximators superior to others? * Can the stability and the convergence of the approximator parameters be guaranteed? * Can control systems be designed to be robust in the face of noise, disturbances, and unmodeled effects? * Can this approach handle significant changes in the dynamics due to such disruptions as system failure? * What types of nonlinear dynamic systems are amenable to this approach? * What are the limitations of adaptive approximation based control? Combining theoretical formulation and design techniques with extensive use of simulation examples, this book is a stimulating text for researchers and graduate students and a valuable resource for practicing engineers.
| Author | : Yury Tiumentsev |
| Publisher | : Academic Press |
| Total Pages | : 334 |
| 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 | : Myer Kutz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 1010 |
| Release | : 2015-02-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1118930835 |
Full coverage of electronics, MEMS, and instrumentation and control in mechanical engineering This second volume of Mechanical Engineers' Handbook covers electronics, MEMS, and instrumentation and control, giving you accessible and in-depth access to the topics you'll encounter in the discipline: computer-aided design, product design for manufacturing and assembly, design optimization, total quality management in mechanical system design, reliability in the mechanical design process for sustainability, life-cycle design, design for remanufacturing processes, signal processing, data acquisition and display systems, and much more. The book provides a quick guide to specialized areas you may encounter in your work, giving you access to the basics of each and pointing you toward trusted resources for further reading, if needed. The accessible information inside offers discussions, examples, and analyses of the topics covered, rather than the straight data, formulas, and calculations you'll find in other handbooks. Presents the most comprehensive coverage of the entire discipline of Mechanical Engineering anywhere in four interrelated books Offers the option of being purchased as a four-book set or as single books Comes in a subscription format through the Wiley Online Library and in electronic and custom formats Engineers at all levels will find Mechanical Engineers' Handbook, Volume 2 an excellent resource they can turn to for the basics of electronics, MEMS, and instrumentation and control.
| Author | : Lei Liu |
| Publisher | : Springer |
| Total Pages | : 443 |
| Release | : 2013-12-19 |
| Genre | : Technology & Engineering |
| ISBN | : 3642363857 |
Applied Methods and Techniques for Mechatronic Systems brings together the relevant studies in mechatronic systems with the latest research from interdisciplinary theoretical studies, computational algorithm development and exemplary applications. Readers can easily tailor the techniques in this book to accommodate their ad hoc applications. The clear structure of each paper, background - motivation - quantitative development (equations) - case studies/illustration/tutorial (curve, table, etc.) is also helpful. It is mainly aimed at graduate students, professors and academic researchers in related fields, but it will also be helpful to engineers and scientists from industry. Lei Liu is a lecturer at Huazhong University of Science and Technology (HUST), China; Quanmin Zhu is a professor at University of the West of England, UK; Lei Cheng is an associate professor at Wuhan University of Science and Technology, China; Yongji Wang is a professor at HUST; Dongya Zhao is an associate professor at China University of Petroleum.
| Author | : |
| Publisher | : |
| Total Pages | : 704 |
| Release | : 1995 |
| Genre | : Aeronautics |
| ISBN | : |
| Author | : A.E. Ruano |
| Publisher | : IET |
| Total Pages | : 478 |
| Release | : 2005-07-18 |
| Genre | : Computers |
| ISBN | : 0863414893 |
Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.
