Time-Varying Constrained Optimization and Robot Optimal Control: A Neurodynamic Approach with NCP Functions
暫譯: 時間變化約束最佳化與機器人最佳控制：基於神經動態的NCP函數方法
Li, Weibing, Li, Yehui, Huang, Kai
- 出版商: CRC
- 出版日期: 2026-08-12
- 售價: $3,270
- 貴賓價: 9.5 折 $3,106
- 語言: 英文
- 頁數: 216
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1041235496
- ISBN-13: 9781041235491
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相關分類:
機器人製作 Robots
尚未上市，無法訂購
相關主題
商品描述
Focusing on error-dynamics-based neurodynamic networks (EDNNs) for optimal control of real-world robots, this book interrogates the application of neurodynamic methods to time-varying constrained optimization (TVCO) problems.
It presents a thorough examination of EDNNs and their applications in TVCO and optimal control of robots. The authors systematically introduce the theoretical foundations, design methodologies, and robotic applications of EDNNs, emphasizing their superiority to traditional optimization solvers. In doing so, this book aims to fill gaps in the application of EDNNs to constrained optimization tasks with a focus on both serial robots (e.g., the Franka Emika Panda robot) and parallel robots (e.g., the Gough-Stewart platform). Key industrial challenges, including obstacle avoidance, joint-limit avoidance, pose control, and high-precision path tracking, are addressed with groundbreaking systematic integration of EDNNs and robot control, as validated by robot simulations and physical experiments.
The book offers practical guidance for researchers and engineers while providing accessible insights for non-specialists, such as librarians and booksellers, on the value of EDNNs in advancing robotic control practices.
商品描述(中文翻譯)
本書專注於基於誤差動力學的神經動態網絡（EDNNs），以實現現實世界機器人的最佳控制，探討神經動態方法在時間變化約束優化（TVCO）問題中的應用。
本書對EDNNs及其在TVCO和機器人最佳控制中的應用進行了徹底的檢視。作者系統地介紹了EDNNs的理論基礎、設計方法論和機器人應用，強調其相較於傳統優化求解器的優越性。通過這樣的方式，本書旨在填補EDNNs在約束優化任務應用中的空白，重點關注串聯機器人（例如，Franka Emika Panda機器人）和並聯機器人（例如，Gough-Stewart平台）。本書針對關鍵的工業挑戰，包括避障、關節限制避免、姿態控制和高精度路徑追蹤，通過EDNNs與機器人控制的開創性系統整合來解決，並通過機器人模擬和實體實驗進行驗證。
本書為研究人員和工程師提供實用指導，同時為非專業人士（如圖書館員和書商）提供關於EDNNs在推進機器人控制實踐中的價值的易懂見解。
作者簡介
Weibing Li is currently an associate professor with the School of Computer Science and Engineering, Sun Yat-sen University. His research interests include robotics and neural networks. He has published more than 130 papers in journals, including IEEE TNNLS, IEEE TMECH, IEEE TSMC, IEEE TCYB, and more.
Yehui Li is currently a postdoctoral fellow with the School of Computer Science and Engineering, Sun Yat-sen University. His research interests include robotics and neural networks. He has published more than 30 papers in journals, including IEEE TMECH, IEEE TSMC, IEEE TBME, IEEE TIM, and more.
Kai Huang is currently a full professor with the School of Computer Science and Engineering, Sun Yat-sen University. His research interests include robotics and real-time systems. He has published more than 100 papers, including Science Robotics, Nature Machine Intelligence, International Journal of Robotics Research, and more.
Yongping Pan is currently a full professor with the School of Automation, Southeast University. His research interests include automatic control and machine learning for robotics. He has authored or co-authored over 200 peer-reviewed academic papers, including IEEE TRO, IEEE TAC, IEEE TNNLS, and more.
作者簡介(中文翻譯)
李維兵目前是中山大學計算機科學與工程學院的副教授。他的研究興趣包括機器人技術和神經網絡。他在期刊上發表了超過130篇論文，包括IEEE TNNLS、IEEE TMECH、IEEE TSMC、IEEE TCYB等。
李業輝目前是中山大學計算機科學與工程學院的博士後研究員。他的研究興趣包括機器人技術和神經網絡。他在期刊上發表了超過30篇論文，包括IEEE TMECH、IEEE TSMC、IEEE TBME、IEEE TIM等。
黃凱目前是中山大學計算機科學與工程學院的正教授。他的研究興趣包括機器人技術和即時系統。他發表了超過100篇論文，包括Science Robotics、Nature Machine Intelligence、International Journal of Robotics Research等。
潘永平目前是東南大學自動化學院的正教授。他的研究興趣包括自動控制和機器人技術的機器學習。他已經撰寫或共同撰寫了超過200篇經過同行評審的學術論文，包括IEEE TRO、IEEE TAC、IEEE TNNLS等。
