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| Author | : Adel Abdel Raouf Hanafy |
| Publisher | : |
| Total Pages | : 268 |
| Release | : 1972 |
| Genre | : Control theory |
| ISBN | : |
| Author | : P. R. Kumar |
| Publisher | : SIAM |
| Total Pages | : 371 |
| Release | : 2015-12-15 |
| Genre | : Mathematics |
| ISBN | : 1611974259 |
Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.
| Author | : K.J. Aström |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 404 |
| Release | : 2012-12-06 |
| Genre | : Science |
| ISBN | : 1441985689 |
The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly stochastic and time-varying systems, their theoretical analysis is usually very difficult. Nevertheless, over the past decade much fundamental progress has been made on some key questions concerning their stability, convergence, performance, and robustness. Moreover, adaptive controllers have been successfully employed in numerous practical applications, and have even entered the marketplace.
| Author | : Jianhua Zhang |
| Publisher | : Academic Press |
| Total Pages | : 320 |
| Release | : 2022-03-15 |
| Genre | : Mathematics |
| ISBN | : 9780128234419 |
Identification and Adaptive Control for Nonlinear Systems and Applications: Applied Mathematics in Control Engineering introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields. The major contribution of the book includes: (1) The basic concepts of nonlinear systems stability analysis and nonlinear systems control method. (2) The stability analysis of complex nonlinear system with adaptive neural networks control. (3) The nonlinear systems adaptive sliding mode controller design of complex nonlinear systems. (4) Some industrial application. The book gives an introduction to basic nonlinear systems architectures for adaptive control methods. Emphasis is placed on the mathematical analysis of these systems, on methods of controlling them for adaptive control and on their application to practical engineering problems in such areas as aircraft path planning. This book enables audience to understand the basic architectures of control science and engineering, and to master classical and advanced design method for nonlinear system. Introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields Presents basic concepts of nonlinear systems stability analysis and nonlinear systems control method Offers practical examples
| Author | : |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2004 |
| Genre | : |
| ISBN | : |
To address Air Force applications, new methods are developed for system identification (ID) and adaptive control. For linear systems, ID algorithms are developed to obtain consistent parameter estimates, stable models, and optimal inputs. Nonlinear ID methods are developed for block-structured models with measured-input nonlinearities. Subspace ID methods are used to identify linear model components, while optimization methods are used to construct efficient basis functions. Specialized methods are developed to identify nonlinear systems with output nonlinearities, limit cycle dynamics, and hysteresis. Adaptive stabilization algorithms are developed for uncertain linear and nonlinear systems under full-state feedback, as well as linear systems with unknown but bounded relative degree. Extensions to discrete-time systems are addressed. Adaptive command-following algorithms are developed for spacecraft and demonstrated on an experimental testbed. Adaptive disturbance rejection algorithms are developed for tonal and broadband disturbances. Nonlinear control algorithms are developed for shape change actuation for spacecraft. Semistability theory is developed to support research in adaptive control.
| Author | : Dr. SHAIK RAFI KIRAN |
| Publisher | : Lulu.com |
| Total Pages | : 118 |
| Release | : |
| Genre | : |
| ISBN | : 1329937201 |
| Author | : Enso Ikonen |
| Publisher | : CRC Press |
| Total Pages | : 328 |
| Release | : 2001-10-02 |
| Genre | : Science |
| ISBN | : 1482294699 |
A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover applications for the identification of linear and non-linear systems, the design of generalized predictive controllers (GPCs), and the control of multivariable
| Author | : Petros Ioannou |
| Publisher | : SIAM |
| Total Pages | : 401 |
| Release | : 2006-01-01 |
| Genre | : Mathematics |
| ISBN | : 0898716152 |
Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index
| 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 | : C.T. Leonides |
| Publisher | : Elsevier |
| Total Pages | : 345 |
| Release | : 2012-12-02 |
| Genre | : Technology & Engineering |
| ISBN | : 0323153496 |
Control and Dynamic Systems: Advances in Theory and Application, Volume 25: System Identification and Adaptive Control, Part 1 of 3 deals with system parameter identification and adaptive control. It presents useful techniques for effective stochastic adaptive control systems. This book discusses multicriteria optimization in adaptive and stochastic control systems. After discussing how to estimate the parameters of an autoregressive moving-average (ARMA) process, it identifies instrumental variable methods for ARMA models. This book also presents robust algorithms for adaptive control; design principles for robustness in adaptive identification methods; utilization of robust smoothing; and order reduction of linear systems. This volume is a useful reference for control systems theorists and practitioners interested in system identification and adaptive control techniques.
