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Design and Implementation of a Novel Neural Fuzzy Control System for a Multi-link Robotic Manipulator

Design and Implementation of a Novel Neural Fuzzy Control System for a Multi-link Robotic Manipulator PDF Author: Limin Peng
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 220

Book Description


Design and Implementation of a Novel Neural Fuzzy Control System for a Multi-link Robotic Manipulator

Design and Implementation of a Novel Neural Fuzzy Control System for a Multi-link Robotic Manipulator PDF Author: Limin Peng
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 220

Book Description


Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities

Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities PDF Author: Frank L. Lewis
Publisher: SIAM
ISBN: 0898715059
Category : Technology & Engineering
Languages : en
Pages : 252

Book Description
Brings neural networks and fuzzy logic together with dynamical control systems. Each chapter presents powerful control approaches for the design of intelligent controllers to compensate for actuator nonlinearities.

Neural Network Control Of Robot Manipulators And Non-Linear Systems

Neural Network Control Of Robot Manipulators And Non-Linear Systems PDF Author: F W Lewis
Publisher: CRC Press
ISBN: 9780748405961
Category : Technology & Engineering
Languages : en
Pages : 470

Book Description
There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.

Bulletin of Pure & Applied Sciences

Bulletin of Pure & Applied Sciences PDF Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 622

Book Description


Fractional Modeling and Controller Design of Robotic Manipulators

Fractional Modeling and Controller Design of Robotic Manipulators PDF Author: Abhaya Pal Singh
Publisher: Springer Nature
ISBN: 3030582477
Category : Technology & Engineering
Languages : en
Pages : 138

Book Description
This book at hand is an appropriate addition to the field of fractional calculus applied to control systems. If an engineer or a researcher wishes to delve into fractional-order systems, then this book has many collections of such systems to work upon, and this book also tells the reader about how one can convert an integer-order system into an appropriate fractional-order one through an efficient and simple algorithm. If the reader further wants to explore the controller design for the fractional-order systems, then for them, this book provides a variety of controller design strategies. The use of fractional-order derivatives and integrals in control theory leads to better results than integer-order approaches and hence provides solid motivation for further development of control theory. Fractional-order models are more useful than the integer-order models when accuracy is of paramount importance. Real-time experimental validation of controller design strategies for the fractional-order plants is available. This book is beneficial to the academic institutes for postgraduate and advanced research-level that need a specific textbook on fractional control and its applications in srobotic manipulators. The book is also a valuable teaching and learning resource for undergraduate and postgraduate students.

Springer Handbook of Computational Intelligence

Springer Handbook of Computational Intelligence PDF Author: Janusz Kacprzyk
Publisher: Springer
ISBN: 3662435055
Category : Technology & Engineering
Languages : en
Pages : 1637

Book Description
The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

High-level Feedback Control With Neural Networks

High-level Feedback Control With Neural Networks PDF Author: Young Ho Kim
Publisher: World Scientific
ISBN: 9814496456
Category : Technology & Engineering
Languages : en
Pages : 228

Book Description
Complex industrial or robotic systems with uncertainty and disturbances are difficult to control. As system uncertainty or performance requirements increase, it becomes necessary to augment traditional feedback controllers with additional feedback loops that effectively “add intelligence” to the system. Some theories of artificial intelligence (AI) are now showing how complex machine systems should mimic human cognitive and biological processes to improve their capabilities for dealing with uncertainty.This book bridges the gap between feedback control and AI. It provides design techniques for “high-level” neural-network feedback-control topologies that contain servo-level feedback-control loops as well as AI decision and training at the higher levels. Several advanced feedback topologies containing neural networks are presented, including “dynamic output feedback”, “reinforcement learning” and “optimal design”, as well as a “fuzzy-logic reinforcement” controller. The control topologies are intuitive, yet are derived using sound mathematical principles where proofs of stability are given so that closed-loop performance can be relied upon in using these control systems. Computer-simulation examples are given to illustrate the performance.

Neural and Fuzzy Logic Control of Drives and Power Systems

Neural and Fuzzy Logic Control of Drives and Power Systems PDF Author: Marcian Cirstea
Publisher: Elsevier
ISBN: 0080497365
Category : Technology & Engineering
Languages : en
Pages : 413

Book Description
The authors guide readers quickly and concisely through the complex topics of neural networks, fuzzy logic, mathematical modelling of electrical machines, power systems control and VHDL design. Unlike the academic monographs that have previously been published on each of these subjects, this book combines them and is based round case studies of systems analysis, control strategies, design, simulation and implementation. The result is a guide to applied control systems design that will appeal equally to students and professional design engineers. The book can also be used as a unique VHDL design aid, based on real-world power engineering applications. Introduces cutting-edge control systems to a wide readership of engineers and students The first book on neuro-fuzzy control systems to take a practical, applications-based approach, backed up with worked examples and case studies Learn to use VHDL in real-world applications

Fuzzy Controller Design

Fuzzy Controller Design PDF Author: Zdenko Kovacic
Publisher: CRC Press
ISBN: 9781420026504
Category : Technology & Engineering
Languages : en
Pages : 424

Book Description
Fuzzy control methods are critical for meeting the demands of complex nonlinear systems. They bestow robust, adaptive, and self-correcting character to complex systems that demand high stability and functionality beyond the capabilities of traditional methods. A thorough treatise on the theory of fuzzy logic control is out of place on the design bench. That is why Fuzzy Controller Design: Theory and Applications offers laboratory- and industry-tested algorithms, techniques, and formulations of real-world problems for immediate implementation. With surgical precision, the authors carefully select the fundamental elements of fuzzy logic control theory necessary to formulate effective and efficient designs. The book supplies a springboard of knowledge, punctuated with examples worked out in MATLAB®/SIMULINK®, from which newcomers to the field can dive directly into applications. It systematically covers the design of hybrid, adaptive, and self-learning fuzzy control structures along with strategies for fuzzy controller design suitable for on-line and off-line operation. Examples occupy an entire chapter, with a section devoted to the simulation of an electro-hydraulic servo system. The final chapter explores industrial applications with emphasis on techniques for fuzzy controller implementation and different implementation platforms for various applications. With proven methods based on more than a decade of experience, Fuzzy Controller Design: Theory and Applications is a concise guide to the methodology, design steps, and formulations for effective control solutions.

Adaptive Neural Network Control Of Robotic Manipulators

Adaptive Neural Network Control Of Robotic Manipulators PDF Author: Sam Shuzhi Ge
Publisher: World Scientific
ISBN: 9814496227
Category : Technology & Engineering
Languages : en
Pages : 397

Book Description
Recently, there has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an “on-and-off” fashion. This book is dedicated to issues on adaptive control of robots based on neural networks. The text has been carefully tailored to (i) give a comprehensive study of robot dynamics, (ii) present structured network models for robots, and (iii) provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.