Physical Generative AIs of Robust Nonlinear Filter and Control Designs for Complicated Man-Made Machines

Bor-Sen Chen received B.S. degree in electrical engineering from Tatung Institute of Technology, Taipei, Taiwan, in 1970, and M.S. degree of geophysics from the National Central University, Chungli, Taiwan in 1973, and Ph.D degree from 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 more than 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 4 Outstanding Research Awards of National Science Council, Academic Award in Engineering from Ministry of Education, National Chair Professor of the Ministry of Education, Best Impact Award of IEEE Taiwan Section for his most SCI citations of IEEE members in Taiwan, etc. 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, physical generative AIs-driven robust nonlinear H∞ filter and control designs of nonlinear dynamic systems, systems medicine design via DNN-based DTI model and design specifications, etc. He is a life fellow of IEEE.

• 1. Introduction to Physical Generative AI-Driven Filter and Control Scheme of Nonlinear Stochastic Systems of Man-Made Machines 2. Physical Generative AI-Driven H∞ Stabilization Control Scheme of Nonlinear Time-Varying Dynamic Systems with Its Application to Quadrotor UAV Tracking Control Design 3. Robust H∞ Physical Generative AI-Driven Filter Design of Nonlinear Stochastic Systems: With Application to Radar Detection of Incoming Missile 4. Physical Generative AI-Driven Mixed H2/H∞ Filter Design of Nonlinear Stochastic Systems for the Trajectory Estimation of Incoming Ballistic Missile 5. Physical Generation AI-Driven Robust H∞ Observer-Based Reference Tracking Control Design of Nonlinear Stochastic Systems with Application to Trajectory Tracking of Quadrotor UAV 6. Physical Generative AI-Driven Mixed H2/H∞ Observer-Based Regulation Control of Nonlinear Stochastic Systems with Application to Anti-Missile Guidance Control System 7. Robust Physical Generative AI-Driven H∞ Attack-Tolerant Localization Filter-Based Path Tracking Control Design of Mobile Robot via Wireless Sensor Networks in the Intelligent Buildings and Smart Cities 8. Physical Generative AI-Driven Decentralized H∞ Team Formation Tracking Control for Large-Scale Biped Robots 9. Physical Generative AI-Driven H∞ Decentralized Attack-Tolerant Observer-Based Team Formation Network Control of Large-Scale Quadrotor UAVs 10. Decentralized H∞ Physical Generative AI-Driven Observer-Based Attack-Tolerant Formation Tracking Network Control of Large-Scale LEO Satellites