Robot Manipulator Control
Robot Manipulator Control

Author: Frank L. Lewis

Publisher: CRC Press

Published: 2003-12-12

Total Pages: 646

ISBN-13: 9780203026953

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Robot Manipulator Control offers a complete survey of control systems for serial-link robot arms and acknowledges how robotic device performance hinges upon a well-developed control system. Containing over 750 essential equations, this thoroughly up-to-date Second Edition, the book explicates theoretical and mathematical requisites for controls design and summarizes current techniques in computer simulation and implementation of controllers. It also addresses procedures and issues in computed-torque, robust, adaptive, neural network, and force control. New chapters relay practical information on commercial robot manipulators and devices and cutting-edge methods in neural network control.

Distributed Adaptive Consensus Control of Uncertain Multi-Agent Systems
Distributed Adaptive Consensus Control of Uncertain Multi-Agent Systems

Author: Wei Wang

Publisher: CRC Press

Published: 2024-08-15

Total Pages: 241

ISBN-13: 1040093833

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Multi-agent systems are special networked systems full of research interest and practical sense, which are abundant in real life, ranging from mobile robot networks, intelligent transportation management, to multiple spacecraft, surveillance and monitoring. Consensus control is one of the most typical and hot research issues for multi-agent systems. Distributed Adaptive Consensus Control of Uncertain Multi-agent Systems provides innovative technologies to design and analyze distributed adaptive consensus for multi-agent systems with model uncertainties. Based on the basic graph theory and adaptive backstepping control, this monograph: · Describes the state of the art on distributed adaptive control, finite-time consensus control and event-triggered consensus control · Studies distributed adaptive consensus under directed communication graph condition: the methods with linearly parametric reference, hierarchical decomposition, and design of auxiliary filers · Explores adaptive finite-time consensus for uncertain nonlinear systems · Considers distributed adaptive consensus with event-triggered communication via state feedback and output feedback · Investigates distributed adaptive formation control of nonholonomic mobile robots with experimental verification · Provides distributed adaptive attitude synchronization control schemes for multiple spacecraft with event-triggered communication Distributed Adaptive Consensus Control of Uncertain Multi-agent Systems can help engineering students and professionals to efficiently learn distributed adaptive control design tool for handling uncertain multi-agent systems with directed communication graph, guaranteeing finite-time convergence and saving communication resources.

Distributed Consensus in Multi-vehicle Cooperative Control
Distributed Consensus in Multi-vehicle Cooperative Control

Author: Wei Ren

Publisher: Springer Science & Business Media

Published: 2007-10-27

Total Pages: 315

ISBN-13: 1848000154

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Assuming only neighbor-neighbor interaction among vehicles, this monograph develops distributed consensus strategies that ensure that the information states of all vehicles in a network converge to a common value. Readers learn to deal with groups of autonomous vehicles in aerial, terrestrial, and submarine environments. Plus, they get the tools needed to overcome impaired communication by using constantly updated neighbor-neighbor interchange.

Cooperative Control of Multi-Agent Systems
Cooperative Control of Multi-Agent Systems

Author: Frank L. Lewis

Publisher: Springer Science & Business Media

Published: 2013-12-31

Total Pages: 315

ISBN-13: 1447155742

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Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs. It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design. Both continuous-time and discrete-time dynamical multi-agent systems are treated. Optimal cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely treated in literature are developed. Results spanning systems with first-, second- and on up to general high-order nonlinear dynamics are presented. Each control methodology proposed is developed by rigorous proofs. All algorithms are justified by simulation examples. The text is self-contained and will serve as an excellent comprehensive source of information for researchers and graduate students working with multi-agent systems.

Optimal Control
Optimal Control

Author: Brian D. O. Anderson

Publisher: Courier Corporation

Published: 2007-02-27

Total Pages: 465

ISBN-13: 0486457664

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Numerous examples highlight this treatment of the use of linear quadratic Gaussian methods for control system design. It explores linear optimal control theory from an engineering viewpoint, with illustrations of practical applications. Key topics include loop-recovery techniques, frequency shaping, and controller reduction. Numerous examples and complete solutions. 1990 edition.

Distributed Coordination of Multi-agent Networks
Distributed Coordination of Multi-agent Networks

Author: Wei Ren

Publisher: Springer Science & Business Media

Published: 2010-11-30

Total Pages: 312

ISBN-13: 0857291696

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Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders.

Adaptive Backstepping Control of Uncertain Systems with Actuator Failures, Subsystem Interactions, and Nonsmooth Nonlinearities
Adaptive Backstepping Control of Uncertain Systems with Actuator Failures, Subsystem Interactions, and Nonsmooth Nonlinearities

Author: Wei Wang

Publisher: CRC Press

Published: 2017-09-18

Total Pages: 287

ISBN-13: 1498776442

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In practice, actuators often undergo failures and various factors influence its effectiveness. Also due to the increasing complexity of large-scale systems, subsystems are often interconnected, whereas the interactions between any two subsystems are difficult to deal with. This book details a series of new methodologies of designing and analyzing adaptive backstepping control systems involving treatment on actuator failures, subsystem interactions and nonsmooth nonlinearities. Moreover, it discusses some interesting open issues in adaptive failure accommodation, decentralized adaptive control and distributed adaptive coordinated control.

Distributed Event-triggered Control
Distributed Event-triggered Control

Author: Zhongkui Li

Publisher: Springer Nature

Published: 2023-12-11

Total Pages: 155

ISBN-13: 9819981700

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This book focuses on distributed event-triggered control of multi-agent systems, in which the event-triggering mechanism is utilized to reduce the communication frequencies in order to compensate for constrained network bandwidths, an aspect that poses significant challenges for distributed control design. The book summarizes the authors’ original, systematic contributions on scalability and robustness, two core issues in distributed event-triggered control. Specifically, the book presents fully distributed adaptive event-triggered control laws; as they rely on neither continuous communications nor global information on the network, these laws are scalable with regard to network size and topology. Moreover, the book provides novel and robust event-triggered algorithms, which can accommodate various frequency-domain and matching uncertainties. The results presented here are applicable to UAV swarms, automobile systems, aerospace systems, vehicle platooning, and more, and will be of considerable interest to graduate students, researchers, and engineers working on network control systems.

Cooperative Control of Multi-Agent Systems
Cooperative Control of Multi-Agent Systems

Author: Zhongkui Li

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 262

ISBN-13: 1466569972

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Distributed controller design is generally a challenging task, especially for multi-agent systems with complex dynamics, due to the interconnected effect of the agent dynamics, the interaction graph among agents, and the cooperative control laws. Cooperative Control of Multi-Agent Systems: A Consensus Region Approach offers a systematic framework for designing distributed controllers for multi-agent systems with general linear agent dynamics, linear agent dynamics with uncertainties, and Lipschitz nonlinear agent dynamics. Beginning with an introduction to cooperative control and graph theory, this monograph: Explores the consensus control problem for continuous-time and discrete-time linear multi-agent systems Studies the H∞ and H2 consensus problems for linear multi-agent systems subject to external disturbances Designs distributed adaptive consensus protocols for continuous-time linear multi-agent systems Considers the distributed tracking control problem for linear multi-agent systems with a leader of nonzero control input Examines the distributed containment control problem for the case with multiple leaders Covers the robust cooperative control problem for multi-agent systems with linear nominal agent dynamics subject to heterogeneous matching uncertainties Discusses the global consensus problem for Lipschitz nonlinear multi-agent systems Cooperative Control of Multi-Agent Systems: A Consensus Region Approach provides a novel approach to designing distributed cooperative protocols for multi-agent systems with complex dynamics. The proposed consensus region decouples the design of the feedback gain matrices of the cooperative protocols from the communication graph and serves as a measure for the robustness of the protocols to variations of the communication graph. By exploiting the decoupling feature, adaptive cooperative protocols are presented that can be designed and implemented in a fully distributed fashion.

Multi-Agent-Based Production Planning and Control
Multi-Agent-Based Production Planning and Control

Author: Jie Zhang

Publisher: John Wiley & Sons

Published: 2017-08-28

Total Pages: 420

ISBN-13: 111889006X

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At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.