Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems write by Kasra Esfandiari. This book was released on 2021-06-18. Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems available in PDF, EPUB and Kindle. The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.
Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems
Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems write by . This book was released on 2004. Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems available in PDF, EPUB and Kindle. The objectives of this research effort were to exploit recent advances in neural network (NN) based adaptive control, with the goal of being able to treat a very general class of nonlinear system, for which the dynamics are not only uncertain, but may in fact be unknown except for minimal structural information, such as the relative degree of the regulated output variables. We were particularly interested in designing adaptive control systems that are robust with respect to both parametric uncertainty and unmodeled dynamics. Extensions to decentralized control were also of interest. In addition, we placed a high priority on transition opportunities in aircraft flight control, control of flows, control of flexible space structures, and control of aeroelastic wings.
Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems
Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems write by Anthony Calise. This book was released on 2001. Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems available in PDF, EPUB and Kindle.
Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems
Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems write by . This book was released on 2001. Neural Network Based Adaptive Control of Uncertain and Unknown Nonlinear Systems available in PDF, EPUB and Kindle. Our main accomplishment this past year has been to finalize and apply two approaches to output feedback adaptive control. The first is a direct adaptive approach, while the second uses a new error state observe. Both approaches overcome the limitation of earlier adaptive state observer based methods, which require that the order of the plant be known, and impose severe restrictions on the relative degree of regulated output variables. Within this context, we also have continued to exploit our approach for adaptive hedging' of actuator limits, which was the highlight of last year's report. We have also made some progress in the area of decentralized adaptive control. Our most significant interactions have been with NASA Marshall, NASA Ames, Wright Patterson AFB, Eglin AFB, Boeing and Lockheed.
Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics
Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics write by Jing Na. This book was released on 2018-06-12. Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics available in PDF, EPUB and Kindle. Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches. This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering. Explains the latest research outputs on modeling, identification and adaptive control for systems with nonsmooth dynamics Provides practical application and experimental results for robotic systems, and servo motors
