Flexible Manipulators

The Intelligent Systems Series comprises titles that present state-of-the-art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. Flexible manipulators play a critical role in applications in a diverse range of fields, such as construction automation, environmental applications, and space engineering. Due to the complexity of the link deformation and dynamics, the research effort on accurate modeling and high performance control of flexible manipulators has increased dramatically in recent years. This book presents analysis, data and insights that will of particular use for researchers and engineers working on the optimization and control of robotic manipulators and automation systems. Government and industry groups have specifically stressed the importance of innovation in robotics, manufacturing automation, and control systems for maintaining innovation and high-value-added manufacturing Discusses the latest research on the quantitative effects of size, shape, mass distribution, tip load, on the dynamics and operational performance of flexible manipulators Presents unique analyses critical to the effective modeling and optimization of manipulators: hard to find data unavailable elsewhere

This book discusses the latest developmens in modelling, simulation and control of flexible robot manipulators. Coverage includes an overall review of previously developed methodologies, a range of modelling approaches including classical techniques, parametric and neuromodelling approaches and numerical modelling/simulation techniques.

Various modelling and control of two-link flexible manipulators are presented in this book. The lumped parameter modelling method and the assumed modes method modelling are comprehensively reviewed. The book also reviews the trajectory tracking problem and tip trajectory tracking problem along with the suppression of tip deflection of the links. An exponential time varying signal and a chaotic signal are considered as the desired trajectories. The identical/ non-identical slave manipulator is synchronised with the controlled master manipulator so that the slave manipulator indirectly follows the desired manipulator.

A manipulator, or 'robot', consists of a series of bodies (links) connected by joints to form a spatial mechanism. Usually the links are connected serially to form an open chain. The joints are either revolute (rotary) or prismatic (telescopic), various combinations of the two giving a wide va riety of possible configurations. Motive power is provided by pneumatic, hydraulic or electrical actuation of the joints. The robot arm is distinguished from other active spatial mechanisms by its reprogrammability. Therefore, the controller is integral to any de scription of the arm. In contrast with many other controlled processes (e. g. batch reactors), it is possible to model the dynamics of a ma nipulator very accurately. Unfortunately, for practical arm designs, the resulting models are complex and a considerable amount of research ef fort has gone into improving their numerical efficiency with a view to real time solution [32,41,51,61,77,87,91]. In recent years, improvements in electric motor technology coupled with new designs, such as direct-drive arms, have led to a rapid increase in the speed and load-carrying capabilities of manipulators. However, this has meant that the flexibility of the nominally rigid links has become increasingly significant. Present generation manipulators are limited to a load-carrying capacity of typically 5-10% of their own weight by the requirement of rigidity. For example, the Cincinatti-Milicron T3R3 robot weighs more than 1800 kg but has a maximum payload capacity of 23 kg.

Flexible robotic manipulators pose various challenges in research as compared to rigid robotic manipulators, ranging from system design, structural optimization, and construction to modeling, sensing, and control. Although significant progress has been made in many aspects over the last one-and-a-half decades, many issues are not resolved yet, and simple, effective, and reliable controls of flexible manipulators still remain an open quest. Clearly, further efforts and results in this area will contribute significantly to robotics (particularly automation) as well as its application and education in general control engineering. To accelerate this process, the leading experts in this important area present in this book the state of the art in advanced studies of the design, modeling, control and applications of flexible manipulators.

This book deals with control and learning in robotic systems.

The book investigates fundamental issues in flexible manipulator systems, including distributed parameter modeling and boundary controller design. It presents theoretical explorations of several fundamental problems concerning the dynamics and control of these systems. By integrating fresh concepts and results to form a systematic approach to control, it also provides a basic theoretical framework. In turn, the book offers a comprehensive treatment of flexible manipulator systems, addressing topics ranging from related distributed parameter modeling and advanced boundary controller design for these systems with input constraint, to active control with output constraint. In brief, the book addresses dynamical analysis and control design for flexible manipulator systems. Though primarily intended for researchers and engineers in the control system and mechanical engineering community, it can also serve as supplemental reading on the modeling and control of flexible manipulator systems at the postgraduate level.