› › Dynamic Modeling And Neural Network Based Intelligent Control Of Flexible Systems

Dynamic Modeling and Neural Network-Based Intelligent Control of Flexible Systems

Author : Hejia Gao

Publisher : Wiley-IEEE Press

Page : 0 pages

File Size : 49,95 MB

Release : 2025-01-02

Category : Technology & Engineering

ISBN : 9781394255276

Get eBook

Book Description

Comprehensive treatment of several representative flexible systems, ranging from dynamic modeling and intelligent control design through to stability analysis Fully illustrated throughout, Dynamic Modeling and Neural Network-Based Intelligent Control of Flexible Systems proposes high-efficiency modeling methods and novel intelligent control strategies for several representative flexible systems developed by means of neural networks. It discusses tracking control of multi-link flexible manipulators, vibration control of flexible buildings under natural disasters, and fault-tolerant control of bionic flexible flapping-wing aircraft and addresses common challenges like external disturbances, dynamic uncertainties, output constraints, and actuator faults. Expanding on its theoretical deliberations, this book includes many case studies demonstrating how the proposed approaches work in practice. Experimental investigations are carried out on Quanser Rotary Flexible Link, Quanser 2 DOF Serial Flexible Link, Quanser Active Mass Damper, and Quanser Smart Structure platforms. This book starts by providing an overview of dynamic modeling and intelligent control of flexible systems, introducing several important issues in the study of flexible systems, along with modeling and control methods of three typical flexible systems. Other topics include: Foundational mathematical preliminaries including the Hamilton principle, model discretization methods, Lagrange's equation method, and Lyapunov's stability theorem Dynamic modeling of a single-link flexible robotic manipulator and vibration control design for a string with the boundary time-varying output constraint Unknown time-varying disturbances, such as earthquakes and strong winds, and how to suppress them and use MATLAB and Quanser to verify effectiveness of a proposed control Adaptive vibration control methods for a single-floor building-like structure equipped with an active mass damper (AMD) Dynamic Modeling and Neural Network-Based Intelligent Control of Flexible Systems is an invaluable resource for researchers and engineers seeking high-efficiency modeling methods and neural-network-based control solutions for flexible systems, along with industry engineers and researchers who are interested in control theory and applications and students in related programs of study.



Intelligent Control Based on Flexible Neural Networks

Author : M. Teshnehlab

Publisher : Springer Science & Business Media

Page : 248 pages

File Size : 16,83 MB

Release : 2013-03-09

Category : Technology & Engineering

ISBN : 9401591873

Get eBook

Book Description

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Chapter 3 Flexible Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . 61 3. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3. 2 Flexible Unipolar Sigmoid Functions . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3. 3 Flexible Bipolar Sigmoid Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3. 4 Learning Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3. 4. 1 Generalized learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3. 4. 2 Specialized learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3. 5 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 3. 6 Combinations of Flexible Artificial Neural Network Topologies . . . . 79 3. 7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Chapter 4 Self-Tuning PID Control 85 4. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4. 2 PID Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4. 3 Flexible Neural Network as an Indirect Controller . . . . . . . . . . . . . . . 91 4. 4 Self-tunig PID Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 4. 5 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4. 5. 1 The Tank model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4. 5. 2 Simulation study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 4. 5. 3 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 4. 6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Chapter 5 Self-Tuning Computed Torque Control: Part I 107 5. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5. 2 Manipulator Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 5. 3 Computed Torque Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5. 4 Self-tunig Computed Torque Control . . . . . . . . . . . . . . . . . . . . . . . . . 111 5. 5 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 5. 5. 1 Simultaneous learning of connection weights and SF para- ters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 5. 5. 2 Learning of the sigmoid function parameters . . . . . . . . . . . . . 123 Vll 5. 5. 3 Simultaneous learning of SF parameters and output gains 129 5. 6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Chapter 6 Self-Tuning Computed Torque Control: Part II 137 6. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 6. 2 Simplification of Flexible Neural Networks . . . . . . . . . . . . . . . . . . . . 138 6. 3 Simulation Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6. 3. 1 Simultaneous learning of connection weights and sigmoid function parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .



Modeling, Simulation, and Control of Flexible Manufacturing Systems

Author : MengChu Zhou

Publisher : World Scientific

Page : 432 pages

File Size : 34,64 MB

Release : 1999

Category : Technology & Engineering

ISBN : 9789810230296

Get eBook

Book Description

One critical barrier leading to successful implementation of flexible manufacturing and related automated systems is the ever-increasing complexity of their modeling, analysis, simulation, and control. Research and development over the last three decades has provided new theory and graphical tools based on Petri nets and related concepts for the design of such systems. The purpose of this book is to introduce a set of Petri-net-based tools and methods to address a variety of problems associated with the design and implementation of flexible manufacturing systems (FMSs), with several implementation examples.There are three ways this book will directly benefit readers. First, the book will allow engineers and managers who are responsible for the design and implementation of modern manufacturing systems to evaluate Petri nets for applications in their work. Second, it will provide sufficient breadth and depth to allow development of Petri-net-based industrial applications. Third, it will allow the basic Petri net material to be taught to industrial practitioners, students, and academic researchers much more efficiently. This will foster further research and applications of Petri nets in aiding the successful implementation of advanced manufacturing systems.



Dynamic Modeling and Boundary Control of Flexible Axially Moving System

Author : Yu Liu

Publisher : Springer Nature

Page : 249 pages

File Size : 49,9 MB

Release : 2023-01-13

Category : Technology & Engineering

ISBN : 9811969418

Get eBook

Book Description

The main objectives of the book are to introduce the design method of boundary control strategies for the axially moving structures to reduce their vibration. This book provides the reader with a thorough grounding in the boundary controller design. Our goal is to provide advanced boundary controller design methods and their stability analysis methods and offer simulation examples and MATLAB programs for each boundary control algorithm. For each chapter, several engineering application examples are given and the contents of each chapter in this book are independent, so that readers can just read their own needs. In this book, all the control algorithms and their programs are described separately and classified by the chapter name, which can be run successfully in MATLAB. The book can benefit researchers, engineers, and graduate students in the fields of PDE modeling and boundary vibration control of flexible structures.



Neural Systems for Control

Author : Omid Omidvar

Publisher : Elsevier

Page : 375 pages

File Size : 44,44 MB

Release : 1997-02-24

Category : Computers

ISBN : 0080537391

Get eBook

Book Description

Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern control theory. The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control for spacecraft aircraft and other systems; applications to rolling mills, robotics and process control; the usage of past output data to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control based on a regulation of physiological investigation/blood pressure control. All researchers and students dealing with control systems will find the fascinating Neural Systems for Control of immense interest and assistance. - Focuses on research in natural and artifical neural systems directly applicable to contol or making use of modern control theory - Represents the most up-to-date developments in this rapidly growing application area of neural networks - Takes a new and novel approach to system identification and synthesis



Control of Flexible-link Manipulators Using Neural Networks

Author : H.A. Talebi

Publisher : Springer Science & Business Media

Page : 172 pages

File Size : 20,94 MB

Release : 2001-01-29

Category : Technology & Engineering

ISBN : 9781852334093

Get eBook

Book Description

Control of Flexible-link Manipulators Using Neural Networks addresses the difficulties that arise in controlling the end-point of a manipulator that has a significant amount of structural flexibility in its links. The non-minimum phase characteristic, coupling effects, nonlinearities, parameter variations and unmodeled dynamics in such a manipulator all contribute to these difficulties. Control strategies that ignore these uncertainties and nonlinearities generally fail to provide satisfactory closed-loop performance. This monograph develops and experimentally evaluates several intelligent (neural network based) control techniques to address the problem of controlling the end-point of flexible-link manipulators in the presence of all the aforementioned difficulties. To highlight the main issues, a very flexible-link manipulator whose hub exhibits a considerable amount of friction is considered for the experimental work. Four different neural network schemes are proposed and implemented on the experimental test-bed. The neural networks are trained and employed as online controllers.



IUTAM Symposium on Intelligent Multibody Systems – Dynamics, Control, Simulation

Author : Evtim Zahariev

Publisher : Springer

Page : 218 pages

File Size : 48,87 MB

Release : 2019-01-09

Category : Technology & Engineering

ISBN : 3030005275

Get eBook

Book Description

This volume, which brings together research presented at the IUTAM Symposium Intelligent Multibody Systems – Dynamics, Control, Simulation, held at Sozopol, Bulgaria, September 11-15, 2017, focuses on preliminary virtual simulation of the dynamics of motion, and analysis of loading of the devices and of their behaviour caused by the working conditions and natural phenomena. This requires up-to-date methods for dynamics analysis and simulation, novel methods for numerical solution of ODE and DAE, real-time simulation, passive, semi-passive and active control algorithms. Applied examples are mechatronic (intelligent) multibody systems, autonomous vehicles, space structures, structures exposed to external and seismic excitations, large flexible structures and wind generators, robots and bio-robots. The book covers the following subjects: -Novel methods in multibody system dynamics; -Real-time dynamics; -Dynamic models of passive and active mechatronic devices; -Vehicle dynamics and control; -Structural dynamics; -Deflection and vibration suppression; -Numerical integration of ODE and DAE for large scale and stiff multibody systems; -Model reduction of large-scale flexible systems. The book will be of interest for scientists and academicians, PhD students and engineers at universities and scientific institutes.



Brain-Inspired Intelligence and Visual Perception

Author : Wenfeng Wang

Publisher : Springer

Page : 177 pages

File Size : 32,59 MB

Release : 2019-02-14

Category : Technology & Engineering

ISBN : 9811335494

Get eBook

Book Description

This book presents the latest findings in the field of brain-inspired intelligence and visual perception (BIVP), and discusses novel research assumptions, including an introduction to brain science and the brain vision hypotheses. Moreover, it introduces readers to the theory and algorithms of BIVP – such as pheromone accumulation and iteration, neural cognitive computing mechanisms, the integration and scheduling of core modules, and brain-inspired perception, motion and control – in a step-by-step manner. Accordingly, it will appeal to university researchers, R&D engineers, undergraduate and graduate students; to anyone interested in robots, brain cognition or computer vision; and to all those wishing to learn about the core theory, principles, methods, algorithms, and applications of BIVP.



Intelligent Automatic Generation Control

Author : Hassan Bevrani

Publisher : CRC Press

Page : 308 pages

File Size : 21,20 MB

Release : 2017-12-19

Category : Technology & Engineering

ISBN : 1439849544

Get eBook

Book Description

Automatic generation control (AGC) is one of the most important control problems in the design and operation of interconnected power systems. Its significance continues to grow as a result of several factors: the changing structure and increasing size, complexity, and functionality of power systems, the rapid emergence (and uncertainty) of renewable energy sources, developments in power generation/consumption technologies, and environmental constraints. Delving into the fundamentals of power system AGC, Intelligent Automatic Generation Control explores ways to make the infrastructures of tomorrow smarter and more flexible. These frameworks must be able to handle complex multi-objective regulation optimization problems, and they must be highly diversified in terms of policies, control strategies, and wide distribution in demand and supply sources—all via an intelligent scheme. The core of such intelligent systems should be based on efficient, adaptable algorithms, advanced information technology, and fast communication devices to ensure that the AGC systems can maintain generation-load balance following serious disturbances. This book addresses several new schemes using intelligent control techniques for simultaneous minimization of system frequency deviation and tie-line power changes, which is required for successful operation of interconnected power systems. It also concentrates on physical and engineering aspects and examines several developed control strategies using real-time simulations. This reference will prove useful for engineers and operators in power system planning and operation, as well as academic researchers and students in field of electrical engineering.



Intelligent Control Systems Using Computational Intelligence Techniques

Author : A.E. Ruano

Publisher : IET

Page : 478 pages

File Size : 23,17 MB

Release : 2005-07-18

Category : Computers

ISBN : 0863414893

Get eBook

Book Description

Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.