Darren M. Dawson – författare

Lyapunov-Based Control of Robotic Systems describes nonlinear control design solutions for problems that arise from robots required to interact with and manipulate their environments. Since most practical scenarios require the design of nonlinear controllers to work around uncertainty and measurement-related issues, the authors use Lyapunov’s direct method as an effective tool to design and analyze controllers for robotic systems.After describing the evolution of real-time control design systems and the associated operating environments and hardware platforms, the book presents a host of standard control design tools for robotic systems using a common Lyapunov-based framework. It then discusses several problems in visual servoing control, including the design of homography-based visual servo control methods and the classic structure from motion problem. The book also deals with the issues of path planning and control for manipulator arms and wheeled mobile robots. With a focus on the emerging research area of human machine interaction, the final chapter illustrates the design of control schemes based on passivity such that the machine is a net energy sink.Including much of the authors’ own research work in controls and robotics, this book facilitates an understanding of the application of Lyapunov-based control design techniques to up-and-coming problems in robotics.

The design of nonlinear controllers for mechanical systems has been an ex­ tremely active area of research in the last two decades. From a theoretical point of view, this attention can be attributed to their interesting dynamic behavior, which makes them suitable benchmarks for nonlinear control the­ oreticians. On the other hand, recent technological advances have produced many real-world engineering applications that require the automatic con­ trol of mechanical systems. the mechanism for de­ Often, Lyapunov-based techniques are utilized as veloping different nonlinear control structures for mechanical systems. The allure of the Lyapunov-based framework for mechanical system control de­ sign can most likely be assigned to the fact that Lyapunov function candi­ dates can often be crafted from physical insight into the mechanics of the system. That is, despite the nonlinearities, couplings, and/or the flexible effects associated with the system, Lyapunov-based techniques can often be used to analyze the stability of the closed-loop system by using an energy­ like function as the Lyapunov function candidate. In practice, the design procedure often tends to be an iterative process that results in the death of many trees. That is, the controller and energy-like function are often constructed in concert to foster an advantageous stability property and/or robustness property. Fortunately, over the last 15 years, many system the­ ory and control researchers have labored in this area to produce various design tools that can be applied in a variety of situations.

Recent advancements in Lyapunov-based design and analysis techniques have applications to a broad class of engineering systems, including mechanical, electrical, robotic, aerospace, and underactuated systems. This book provides a practical yet rigorous development of nonlinear, Lyapunov-based tools and their use in the solution of control-theoretic problems. Rich in motivating examples and new design techniques, the text balances theoretical foundations and real-world implementation. Features include: * Control designs for a broad class of engineering systems * Presentation of adaptive and learning control methods for uncertain nonlinear systems * Experimental testbed descriptions and results that guide the reader toward techniques for further research * Development of necessary mathematical background in each chapter; additional mathematical prerequisites contained in two appendices Intended for readers who have some knowledge of undergraduate systems theory, the book includes a wide range of applications making it suitable for an extensive audience. Graduate students and researchers in control systems, robotics, and applied mathematics, as well as professional engineers will appreciate the work's combination of theoretical underpinnings and current and emerging engineering applications.

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.

Lyapunov-Based Control of Robotic Systems describes nonlinear control design solutions for problems that arise from robots required to interact with and manipulate their environments. Since most practical scenarios require the design of nonlinear controllers to work around uncertainty and measurement-related issues, the authors use Lyapunov’s direct method as an effective tool to design and analyze controllers for robotic systems.After describing the evolution of real-time control design systems and the associated operating environments and hardware platforms, the book presents a host of standard control design tools for robotic systems using a common Lyapunov-based framework. It then discusses several problems in visual servoing control, including the design of homography-based visual servo control methods and the classic structure from motion problem. The book also deals with the issues of path planning and control for manipulator arms and wheeled mobile robots. With a focus on the emerging research area of human machine interaction, the final chapter illustrates the design of control schemes based on passivity such that the machine is a net energy sink.Including much of the authors’ own research work in controls and robotics, this book facilitates an understanding of the application of Lyapunov-based control design techniques to up-and-coming problems in robotics.

Recent advancements in Lyapunov-based design and analysis techniques have applications to a broad class of engineering systems, including mechanical, electrical, robotic, aerospace, and underactuated systems. This book provides a practical yet rigorous development of nonlinear, Lyapunov-based tools and their use in the solution of control-theoretic problems. Rich in motivating examples and new design techniques, the text balances theoretical foundations and real-world implementation. Features include: * Control designs for a broad class of engineering systems * Presentation of adaptive and learning control methods for uncertain nonlinear systems * Experimental testbed descriptions and results that guide the reader toward techniques for further research * Development of necessary mathematical background in each chapter; additional mathematical prerequisites contained in two appendices Intended for readers who have some knowledge of undergraduate systems theory, the book includes a wide range of applications making it suitable for an extensive audience. Graduate students and researchers in control systems, robotics, and applied mathematics, as well as professional engineers will appreciate the work's combination of theoretical underpinnings and current and emerging engineering applications.

The design of nonlinear controllers for mechanical systems has been an ex­ tremely active area of research in the last two decades. From a theoretical point of view, this attention can be attributed to their interesting dynamic behavior, which makes them suitable benchmarks for nonlinear control the­ oreticians. On the other hand, recent technological advances have produced many real-world engineering applications that require the automatic con­ trol of mechanical systems. the mechanism for de­ Often, Lyapunov-based techniques are utilized as veloping different nonlinear control structures for mechanical systems. The allure of the Lyapunov-based framework for mechanical system control de­ sign can most likely be assigned to the fact that Lyapunov function candi­ dates can often be crafted from physical insight into the mechanics of the system. That is, despite the nonlinearities, couplings, and/or the flexible effects associated with the system, Lyapunov-based techniques can often be used to analyze the stability of the closed-loop system by using an energy­ like function as the Lyapunov function candidate. In practice, the design procedure often tends to be an iterative process that results in the death of many trees. That is, the controller and energy-like function are often constructed in concert to foster an advantageous stability property and/or robustness property. Fortunately, over the last 15 years, many system the­ ory and control researchers have labored in this area to produce various design tools that can be applied in a variety of situations.