The aim of this book is to provide insight on the vibration problem in structurally flexible mechanisms, particularly robotic manipulators. The book covers different aspects of flexible structures. It partially includes the fundamental formulations for modelling of a flexible structure actuated with piezoelectric actuators. Mathematical modelling, when possible, as well as experimental techniques for obtaining models of flexible structures are discussed. Additionally, different control techniques adapted for flexible robotic manipulators equipped with piezoelectric actuators and sensors are covered in the book. Depending on the system, linear and non-linear control techniques for stabilising residual vibrations in the system are discussed.
Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
An important obstacle in Minimally Invasive Surgery (MIS) is the significant degradation of haptic feedback (sensation of touch) to the surgeon about surgical instrument's interaction with tissue. This monograph is concerned with devices and methods required for incorporating haptic feedback in master-slave robotic MIS systems. In terms of devices, novel mechanisms are designed including a surgical end-effector (slave) with full force sensing capabilities and a surgeon-robot interface (master) with full force feedback capabilities. Using the master-slave system, various haptic teleoperation control schemes are compared in terms of stability and performance, and passivity-based time delay compensation for haptic teleoperation over a long distance is investigated. The monograph also compares haptic feedback with visual feedback and with substitution for haptic feedback by other sensory cues in terms of surgical task performance.
This monograph provides a comprehensive and thorough treatment of the problem of controlling a redundant robot manipulator. It presents the latest research from the field with a good balance between theory and practice. All theoretical developments are verified both via simulation and experimental work on an actual prototype redundant robot manipulator. This book is the first text aimed at graduate students and researchers working in the area of redundant manipulators giving a comprehensive coverage of control of redundant robot manipulators from the viewpoint of theory and experimentation.
Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
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