Dynamic Neural Networks for Motion Control of Redundant Manipulators (eBook)

Renpeng Huang, Mei Liu, Jingkun Yan (Autoren)

eBook Download: PDF

2025
226 Seiten
Springer Nature Singapore (Verlag)
978-981-96-9144-9 (ISBN)

Infos

This book discusses the development and application of dynamic neural networks (DNNs) for solving complex motion control problems in redundant manipulators. Specifically, it presents a series of advanced DNNs, including noise-rejection DNNs, fuzzy-parameter DNNs, and so on, which are designed to optimize performance while ensuring robustness and computational efficiency. Based on the presented DNNs, this book further constructs a series of motion control schemes for redundant manipulators to address some key challenges such as cyclic motion, position and orientation tracking, and model-unknown scenarios. Each method is rigorously demonstrated for the convergence, and its effectiveness is validated through simulations and physical experiments. By integrating computational intelligence with control theory, this book provides a comprehensive framework for solving time-varying and noise-perturbed problems in robotics, making it a valuable resource for researchers and practitioners in the field.

Produkt-Details

• Erscheint lt. Verlag: 30.9.2025
• Reihe/Serie: Intelligent Control and Learning Systems
• Zusatzinfo: XVI, 226 p. 72 illus., 67 illus. in color.
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Schlagworte: dynamical neural networks • Motion Control • neural dynamics • noise-rejection • redundant manipulators
• ISBN-10: 981-96-9144-3 / 9819691443
• ISBN-13: 978-981-96-9144-9 / 9789819691449