Industrial automation is advancing the use of robot manipulators, with research increasingly focused on the benefits of flexible manipulators over rigid ones. This book presents recent progress and new developments in the analysis and control of flexible robot manipulators.
Following an overview of flexible manipulators, the book covers various modeling and simulation methods, including Lagrange equation-based techniques, parametric approaches using system identification, neuro-modelling, and numerical methods like finite difference and finite element analysis. It then explores a range of control strategies, from open-loop and closed-loop methods—both classical and modern—to neuro and iterative control, as well as soft-computing techniques such as fuzzy logic, neural networks, and evolutionary or bio-inspired optimization. The book also introduces SCEFMAS, a software platform for the analysis, design, simulation, and control of flexible manipulators.
Flexible Robot Manipulators is essential reading for advanced students in robotics, mechatronics, and control engineering, and serves as a valuable reference for research on modeling, simulation, and control of dynamic flexible structures, especially flexible robotic manipulators.
