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| Author | : Yungsun Hahn |
| Publisher | : |
| Total Pages | : 380 |
| Release | : 1990 |
| Genre | : Adaptive control systems |
| ISBN | : |
| Author | : Nikolai Michailovich Filatov |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 258 |
| Release | : 2004-04-20 |
| Genre | : Technology & Engineering |
| ISBN | : 9783540213734 |
This monograph demonstrates how the performance of various well-known adaptive controllers can be improved significantly using the dual effect. The modifications to incorporate dual control are realized separately and independently of the main adaptive controller without complicating the algorithms. A new bicriterial approach for dual control is developed and applied to various types of popular linear and nonlinear adaptive controllers. Practical applications of the designed controllers to several real-time problems are presented. This monograph is the first book providing a complete exposition on the dual control problem from the inception in the early 1960s to the present state of the art aiming at students and researchers in adaptive control as well as design engineers in industry.
| Author | : |
| Publisher | : |
| Total Pages | : 13 |
| Release | : 1988 |
| Genre | : |
| ISBN | : |
Following a set up investigated by Rishel we consider an adaptive control problem with unknown parameter x as a partially observed stochastic control problem. Exploiting the finite dimensionality of the estimator, we transform it to a fully observed stochastic optimal control problem to which we then find epsilon-optimal randomized feedback policies.
| Author | : Simon G. Fabri |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 275 |
| Release | : 2012-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 144710319X |
Unique in its systematic approach to stochastic systems, this book presents a wide range of techniques that lead to novel strategies for effecting intelligent control of complex systems that are typically characterised by uncertainty, nonlinear dynamics, component failure, unpredictable disturbances, multi-modality and high dimensional spaces.
| Author | : |
| Publisher | : |
| Total Pages | : 602 |
| Release | : 1995 |
| Genre | : Aeronautics |
| ISBN | : |
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
| Author | : Arunabha Bagchi |
| Publisher | : |
| Total Pages | : 30 |
| Release | : 1994 |
| Genre | : |
| 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 | : Alexis Aloneftis |
| Publisher | : Springer |
| Total Pages | : 144 |
| Release | : 1987 |
| Genre | : Language Arts & Disciplines |
| ISBN | : |
The theme of this monograph is the adaptive control of systems in a stochastic environment and, more precisely, the study of the tracking problem for ARMAX SISO stochastic systems with time invariant and time varying parameters. Results of simultaneous tracking and parameter identification are included. The author has aimed to (1) provide a reasonably self-contained and up-to-date exposition of the tracking problem after having properly placed it amongst numerous ideas, approaches, and subproblems related to adaptive control, (2) display computer simulation results and discuss their comparative behaviour, (3) introduce a new approach to the stochastic adaptive control with promising results, and (4) qualitatively discuss the adaptive control problem in the hope of improving our understanding of it, stimulate the informed reader to come up with new ideas, and attract newcomers to its study. The reader is assumed to have studied control systems at the graduate level and to have a reasonably good grasp of basic probability theory. Apart from its educational value to the adaptive control student, it is hoped that the accumulation of scattered results and their computer simulation, as well as an extensive reference section will attract the active researcher in this field.
| Author | : Tsan-Ming Choi |
| Publisher | : Springer |
| Total Pages | : 281 |
| Release | : 2017-05-04 |
| Genre | : Business & Economics |
| ISBN | : 3319535188 |
This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This “big data” provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.
| Author | : Peter S. Maybeck |
| Publisher | : Academic Press |
| Total Pages | : 311 |
| Release | : 1982-08-25 |
| Genre | : Mathematics |
| ISBN | : 0080960030 |
This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.
