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Modeling and Nonlinear Robust Control of Delta-Like Parallel Kinematic Manipulators: Emerging Methodologies and Applications in Modelling, Identification and Control

Autor Jonatan Martin Escorcia Hernandez, Ahmed Chemori, Hipolito Aguilar Sierra
en Limba Engleză Paperback – 17 ian 2023
Modeling and Nonlinear Robust Control of Delta-Like Parallel Kinematic Manipulators deals with the modeling and control of parallel robots. The book's content will benefit students, researchers and engineers in robotics by providing a simplified methodology to obtain the dynamic model of parallel robots with a delta-type architecture. Moreover, this methodology is compatible with the real-time implementation of model-based and robust control schemes. And, it can easily extend the proposed robust control solutions to other robotic architectures.

  • Introduces a novel parallel robot designed for machining operations called SPIDER4
  • Presents a mathematical formulation of the kinematic and dynamic models of SPIDER4
  • Offers validation of the computed mathematical models and designed controllers through real-time experiments under different operating conditions
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Specificații

ISBN-13: 9780323961011
ISBN-10: 0323961010
Pagini: 170
Dimensiuni: 152 x 229 x 14 mm
Greutate: 0.24 kg
Editura: ELSEVIER SCIENCE
Seria Emerging Methodologies and Applications in Modelling, Identification and Control


Public țintă

Ph.D. students and researchers in robotics centered around parallel robots.
Robotics engineers, robotics researchers in general, and undergraduate, graduate, researchers from other robotics areas, since the control schemes presented in this book can be applied to other types of robotic manipulators

Cuprins

1. Introduction
2. Literature review about modelling and control of PKMs
3. Description and Modelling of Experimental platforms
4. Proposed Robust Control Solutions
5. Numerical simulations and Real-time experiments
General Conclusion
Appendices
A Proof of lemma 1
B Trajectory points for SPIDER4
B1 Trajectory points for Scenario 1
B2 Trajectory points for scenario 2