Physics-Generated AIs of Robust Nonlinear Filter and Control Designs for Complicated Man-Made Machines
暫譯: 物理生成的強健非線性濾波器與控制設計的人工智慧應用於複雜人造機器
Chen, Bor-Sen
相關主題
商品描述
This book introduces a robust H∞ physics-generated AI-driven filter and controller, along with a nonlinear Luenberger observer model and a state estimation error dynamic model, to effectively address HJIEs for robust H∞ state estimation (filtering) and reference trajectory tracking control in nonlinear stochastic systems. Additionally, it presents a method for training deep neural networks (DNNs) using these models, alongside a physics-generated AI-driven observer-based reference tracking control scheme, with applications in the guidance and control of relevant systems.
Key features:
- Provides theoretical analysis and detailed design procedure for physics-generated AI-driven H∞ or mixed H2/H∞ filter
- Applies physics-generated AI-driven robust H∞ or mixed H2/H∞ filter and reference tracking control schemes to the trajectory estimation and reference tracking control of man-made machines
- Introduces physics-generated AI-driven decentralized H∞ observer-based team formation tracking control of large-scale quadrotor UAVs, biped robots or LEO satellites
- Promulgates the idea of the forthcoming age of physics-generated AI in robot
- Describes robust physics-generated AI-driven filter and control schemes for complex man-made machines
This book is aimed at graduate students and researchers in control science, signal processing and artificial intelligence.
商品描述(中文翻譯)
這本書介紹了一種穩健的 H∞ 物理生成的 AI 驅動濾波器和控制器，以及一個非線性 Luenberger 觀測器模型和狀態估計誤差動態模型，以有效解決非線性隨機系統中的 HJIEs，實現穩健的 H∞ 狀態估計（濾波）和參考軌跡跟踪控制。此外，它還提出了一種使用這些模型訓練深度神經網絡（DNNs）的方法，以及一種基於物理生成的 AI 驅動觀測器的參考跟踪控制方案，應用於相關系統的引導和控制。
主要特點：
- 提供物理生成的 AI 驅動 H∞ 或混合 H2/H∞ 濾波器的理論分析和詳細設計程序
- 將物理生成的 AI 驅動穩健 H∞ 或混合 H2/H∞ 濾波器和參考跟踪控制方案應用於人造機器的軌跡估計和參考跟踪控制
- 介紹物理生成的 AI 驅動去中心化 H∞ 觀測器基於大型四旋翼無人機、雙足機器人或低地球軌道衛星的團隊形成跟踪控制
- 宣揚即將到來的物理生成 AI 在機器人領域的時代
- 描述針對複雜人造機器的穩健物理生成 AI 驅動濾波器和控制方案
這本書的目標讀者是控制科學、信號處理和人工智慧的研究生和研究人員。
作者簡介
Bor-Sen Chen received his BS in electrical engineering from Tatung Institute of Technology, Taipei, Taiwan, in 1970, and MS in geophysics from National Central University, Chungli, Taiwan, in 1973, and PhD from the University of Southern California, Los Angeles, CA, USA, in 1982. From 1973 to 1987, he had been a lecturer, associate professor and professor of Tatung Institute of Technology. From 1987, he has been a professor, chair professor and Tsing Hua distinguished chair professor with the Department of Electrical Engineering of National Tsing Hua University, Hsinchu, Taiwan. His research interests include robust control theory and engineering design, robust signal processing and communication system design, systems biology and their applications. He has published over 370 journal papers, including 140 papers in control, 80 papers in signal processing and communication and 120 papers in systems biology. He has also published 14 monographs. He was the recipient of numerous awards for his academic accomplishments in robust control, fuzzy control, H∞ control, stochastic control, signal processing and systems biology, including four Outstanding Research Awards of National Science Council, Academic Award in Engineering from Ministry of Education, National Chair Professor of the Ministry of Education and Best Impact Award of IEEE Taiwan Section for his most SCI citations of IEEE members in Taiwan. His current research interest focuses on the H∞ team formation network tracking control of large-scale UAVs, large-scale biped robots and their team cooperation, physics-generated AI-driven robust nonlinear H∞ filter and control designs of nonlinear dynamic systems, systems medicine design via DNN-based DTI model and design specifications. He is a life fellow of IEEE. Professor Chen is a 1% scientist according to the World's Top 2% Scientists of Stanford University.
作者簡介(中文翻譯)
陳博森於1970年在台灣台北的大同技術學院獲得電機工程學士學位，1973年在台灣中壢的國立中央大學獲得地球物理學碩士學位，並於1982年在美國加州洛杉磯的南加州大學獲得博士學位。從1973年到1987年，他曾擔任大同技術學院的講師、副教授及教授。自1987年起，他在國立清華大學電機工程學系擔任教授、講座教授及清華特聘講座教授。他的研究興趣包括穩健控制理論與工程設計、穩健信號處理與通信系統設計、系統生物學及其應用。他已發表超過370篇期刊論文，其中包括140篇控制領域的論文、80篇信號處理與通信的論文以及120篇系統生物學的論文。他還出版了14本專著。他因在穩健控制、模糊控制、H∞控制、隨機控制、信號處理和系統生物學方面的學術成就獲得多項獎項，包括四次國家科學委員會的傑出研究獎、教育部的工程學術獎、教育部的國家講座教授及IEEE台灣區最佳影響獎，以表彰他在台灣IEEE會員中最高的SCI引用次數。他目前的研究興趣集中在大規模無人機的H∞團隊形成網絡跟踪控制、大規模雙足機器人及其團隊合作、物理生成的AI驅動穩健非線性H∞濾波器及非線性動態系統的控制設計、基於DNN的DTI模型的系統醫學設計及設計規範。他是IEEE的終身會士。根據史丹佛大學的世界前2%科學家名單，陳教授被認為是1%的科學家。
