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| Author | : Joy H. Kelly |
| Publisher | : |
| Total Pages | : 312 |
| Release | : 1992 |
| Genre | : Adaptive control systems |
| ISBN | : |
| Author | : Anh Tuan Le |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 364 |
| Release | : 2018-03-07 |
| Genre | : Technology & Engineering |
| ISBN | : 9535137964 |
This book focuses on the applications of robust and adaptive control approaches to practical systems. The proposed control systems hold two important features: (1) The system is robust with the variation in plant parameters and disturbances (2) The system adapts to parametric uncertainties even in the unknown plant structure by self-training and self-estimating the unknown factors. The various kinds of robust adaptive controls represented in this book are composed of sliding mode control, model-reference adaptive control, gain-scheduling, H-infinity, model-predictive control, fuzzy logic, neural networks, machine learning, and so on. The control objects are very abundant, from cranes, aircrafts, and wind turbines to automobile, medical and sport machines, combustion engines, and electrical machines.
| Author | : Petros Ioannou |
| Publisher | : Courier Corporation |
| Total Pages | : 850 |
| Release | : 2013-09-26 |
| Genre | : Technology & Engineering |
| ISBN | : 0486320723 |
Presented in a tutorial style, this comprehensive treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Numerous examples clarify procedures and methods. 1995 edition.
| Author | : Bin Yao |
| Publisher | : |
| Total Pages | : 552 |
| Release | : 1996 |
| Genre | : Nonlinear control theory |
| ISBN | : |
| Author | : Weizhong Lu |
| Publisher | : |
| Total Pages | : 134 |
| Release | : 1992 |
| Genre | : Adaptive control systems |
| ISBN | : |
| Author | : Spandan Roy |
| Publisher | : Springer Nature |
| Total Pages | : 157 |
| Release | : 2019-10-08 |
| Genre | : Technology & Engineering |
| ISBN | : 981150640X |
The book investigates the role of artificial input delay in approximating unknown system dynamics, referred to as time-delayed control (TDC), and provides novel solutions to current design issues in TDC. Its central focus is on designing adaptive-switching gain-based robust control (ARC) for a class of Euler–Lagrange (EL) systems with minimal or no knowledge of the system dynamics parameters. The newly proposed TDC-based ARC tackles the commonly observed over- and under-estimation issues in switching gain. The consideration of EL systems lends a practical perspective on the proposed methods, and each chapter is supplemented by relevant experimental data. The book offers a unique resource for researchers in the areas of ARC and TDC alike, and covers the state of the art, new algorithms, and future directions.
| Author | : Le Anh Tuan |
| Publisher | : |
| Total Pages | : 362 |
| Release | : 2018 |
| Genre | : Mechanical engineering and machinery |
| ISBN | : 9789535140702 |
This book focuses on the applications of robust and adaptive control approaches to practical systems. The proposed control systems hold two important features: (1) The system is robust with the variation in plant parameters and disturbances (2) The system adapts to parametric uncertainties even in the unknown plant structure by self-training and self-estimating the unknown factors. The various kinds of robust adaptive controls represented in this book are composed of sliding mode control, model-reference adaptive control, gain-scheduling, H-infinity, model-predictive control, fuzzy logic, neural networks, machine learning, and so on. The control objects are very abundant, from cranes, aircrafts, and wind turbines to automobile, medical and sport machines, combustion engines, and electrical machines.
| 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 | : Chih Jeun Khoh |
| Publisher | : |
| Total Pages | : 178 |
| Release | : 2000 |
| Genre | : |
| ISBN | : |
| Author | : Mo Jamshidi |
| Publisher | : CRC Press |
| Total Pages | : 232 |
| Release | : 2018-10-03 |
| Genre | : Technology & Engineering |
| ISBN | : 1420058347 |
In recent years, new paradigms have emerged to replace-or augment-the traditional, mathematically based approaches to optimization. The most powerful of these are genetic algorithms (GA), inspired by natural selection, and genetic programming, an extension of GAs based on the optimization of symbolic codes. Robust Control Systems with Genetic Algorithms builds a bridge between genetic algorithms and the design of robust control systems. After laying a foundation in the basics of GAs and genetic programming, it demonstrates the power of these new tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control. It also explores the application of hybrid approaches: how to enhance genetic algorithms and programming with fuzzy logic to design intelligent control systems. The authors consider a variety of applications, such as the optimal control of robotic manipulators, flexible links and jet engines, and illustrate a multi-objective, genetic algorithm approach to the design of robust controllers with a gasification plant case study. The authors are all masters in the field and clearly show the effectiveness of GA techniques. Their presentation is your first opportunity to fully explore this cutting-edge approach to robust optimal control system design and exploit its methods for your own applications.
