Neural Network-Based State Estimation of Nonlinear Systems

Neural Network-Based State Estimation of Nonlinear Systems
Author: Heidar A. Talebi
Publisher: Springer
Total Pages: 166
Release: 2009-12-04
Genre: Technology & Engineering
ISBN: 1441914382

"Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems
Author: Kasra Esfandiari
Publisher: Springer Nature
Total Pages: 181
Release: 2021-06-18
Genre: Technology & Engineering
ISBN: 3030731367

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.

Differential Neural Networks for Robust Nonlinear Control

Differential Neural Networks for Robust Nonlinear Control
Author: Alexander S. Poznyak
Publisher: World Scientific
Total Pages: 455
Release: 2001
Genre: Computers
ISBN: 9810246242

This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.).

State Estimation and Stabilization of Nonlinear Systems

State Estimation and Stabilization of Nonlinear Systems
Author: Abdellatif Ben Makhlouf
Publisher: Springer Nature
Total Pages: 439
Release: 2023-11-06
Genre: Technology & Engineering
ISBN: 3031379705

This book presents the separation principle which is also known as the principle of separation of estimation and control and states that, under certain assumptions, the problem of designing an optimal feedback controller for a stochastic system can be solved by designing an optimal observer for the system's state, which feeds into an optimal deterministic controller for the system. Thus, the problem may be divided into two halves, which simplifies its design. In the context of deterministic linear systems, the first instance of this principle is that if a stable observer and stable state feedback are built for a linear time-invariant system (LTI system hereafter), then the combined observer and feedback are stable. The separation principle does not true for nonlinear systems in general. Another instance of the separation principle occurs in the context of linear stochastic systems, namely that an optimum state feedback controller intended to minimize a quadratic cost is optimal for the stochastic control problem with output measurements. The ideal solution consists of a Kalman filter and a linear-quadratic regulator when both process and observation noise are Gaussian. The term for this is linear-quadratic-Gaussian control. More generally, given acceptable conditions and when the noise is a martingale (with potential leaps), a separation principle, also known as the separation principle in stochastic control, applies when the noise is a martingale (with possible jumps).

Artificial Higher Order Neural Networks for Modeling and Simulation

Artificial Higher Order Neural Networks for Modeling and Simulation
Author: Zhang, Ming
Publisher: IGI Global
Total Pages: 455
Release: 2012-10-31
Genre: Computers
ISBN: 1466621761

"This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.

Network and Communication Technology Innovations for Web and IT Advancement

Network and Communication Technology Innovations for Web and IT Advancement
Author: Alkhatib, Ghazi I.
Publisher: IGI Global
Total Pages: 455
Release: 2012-10-31
Genre: Computers
ISBN: 1466621583

With the steady stream of new web based information technologies being introduced to organizations, the need for network and communication technologies to provide an easy integration of knowledge and information sharing is essential. Network and Communication Technology Innovations for Web and IT Advancement presents studies on trends, developments, and methods on information technology advancements through network and communication technology. This collection brings together integrated approaches for communication technology and usage for web and IT advancements.

Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach

Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach
Author: Ehsan Sobhani-Tehrani
Publisher: Springer Science & Business Media
Total Pages: 275
Release: 2009-06-22
Genre: Technology & Engineering
ISBN: 0387929061

Theincreasingcomplexityofspacevehiclessuchassatellites,andthecostreduction measures that have affected satellite operators are increasingly driving the need for more autonomy in satellite diagnostics and control systems. Current methods for detecting and correcting anomalies onboard the spacecraft as well as on the ground are primarily manual and labor intensive, and therefore, tend to be slow. Operators inspect telemetry data to determine the current satellite health. They use various statisticaltechniques andmodels,buttheanalysisandevaluation ofthelargevolume of data still require extensive human intervention and expertise that is prone to error. Furthermore, for spacecraft and most of these satellites, there can be potentially unduly long delays in round-trip communications between the ground station and the satellite. In this context, it is desirable to have onboard fault-diagnosis system that is capable of detecting, isolating, identifying or classifying faults in the system withouttheinvolvementandinterventionofoperators.Towardthisend,theprinciple goal here is to improve the ef?ciency, accuracy, and reliability of the trend analysis and diagnostics techniques through utilization of intelligent-based and hybrid-based methodologies.

Analysis and Synthesis of Fault-Tolerant Control Systems

Analysis and Synthesis of Fault-Tolerant Control Systems
Author: Magdi S. Mahmoud
Publisher: John Wiley & Sons
Total Pages: 451
Release: 2013-10-28
Genre: Technology & Engineering
ISBN: 111870035X

In recent years, control systems have become more sophisticated in order to meet increased performance and safety requirements for modern technological systems. Engineers are becoming more aware that conventional feedback control design for a complex system may result in unsatisfactory performance, or even instability, in the event of malfunctions in actuators, sensors or other system components. In order to circumvent such weaknesses, new approaches to control system design have emerged which can tolerate component malfunctions while maintaining acceptable stability and performance. These types of control systems are often known as fault-tolerant control systems (FTCS). More precisely, FTCS are control systems which possess the ability to accommodate component failure automatically. Analysis and Synthesis of Fault-Tolerant Control Systems comprehensively covers the analysis and synthesis methods of fault tolerant control systems. It unifies the methods for developing controllers and filters for a wide class of dynamical systems and reports on the recent technical advances in design methodologies. MATLAB® is used throughout the book, to demonstrate methods of analysis and design. Key features: • Provides advanced theoretical methods and typical practical applications • Provides access to a spectrum of control design methods applied to industrial systems • Includes case studies and illustrative examples • Contains end-of-chapter problems Analysis and Synthesis of Fault-Tolerant Control Systems is a comprehensive reference for researchers and practitioners working in this area, and is also a valuable source of information for graduates and senior undergraduates in control, mechanical, aerospace, electrical and mechatronics engineering departments.

Emerging Capabilities and Applications of Artificial Higher Order Neural Networks

Emerging Capabilities and Applications of Artificial Higher Order Neural Networks
Author: Zhang, Ming
Publisher: IGI Global
Total Pages: 540
Release: 2021-02-05
Genre: Computers
ISBN: 1799835650

Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted and used by individuals working in information science, information technology, management, economics, and business fields. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks contains innovative research on how to use HONNs in control and recognition areas and explains why HONNs can approximate any nonlinear data to any degree of accuracy, their ease of use, and how they can have better nonlinear data recognition accuracy than SAS nonlinear procedures. Featuring coverage on a broad range of topics such as nonlinear regression, pattern recognition, and data prediction, this book is ideally designed for data analysists, IT specialists, engineers, researchers, academics, students, and professionals working in the fields of economics, business, modeling, simulation, control, recognition, computer science, and engineering research.

State Estimation Strategies in Lithium-ion Battery Management Systems

State Estimation Strategies in Lithium-ion Battery Management Systems
Author: Kailong Liu
Publisher: Elsevier
Total Pages: 377
Release: 2023-07-14
Genre: Technology & Engineering
ISBN: 0443161615

State Estimation Strategies in Lithium-ion Battery Management Systems presents key technologies and methodologies in modeling and monitoring charge, energy, power and health of lithium-ion batteries. Sections introduce core state parameters of the lithium-ion battery, reviewing existing research and the significance of the prediction of core state parameters of the lithium-ion battery and analyzing the advantages and disadvantages of prediction methods of core state parameters. Characteristic analysis and aging characteristics are then discussed. Subsequent chapters elaborate, in detail, on modeling and parameter identification methods and advanced estimation techniques in different application scenarios. Offering a systematic approach supported by examples, process diagrams, flowcharts, algorithms, and other visual elements, this book is of interest to researchers, advanced students and scientists in energy storage, control, automation, electrical engineering, power systems, materials science and chemical engineering, as well as to engineers, R&D professionals, and other industry personnel. - Introduces lithium-ion batteries, characteristics and core state parameters - Examines battery equivalent modeling and provides advanced methods for battery state estimation - Analyzes current technology and future opportunities