
Physical Generative Ais of Robust Nonlinear Filter and Control Designs for Complicated Man-Made Machines
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This book introduces a robust H¿ physical generative 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 physical generative AI-driven observer-based reference tracking control scheme, with applications in the guidance and control of relevant systems. Key features- -Pr...
This book introduces a robust H¿ physical generative 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 physical generative 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 physical generative AI-driven H¿ or mixed H2/H¿ filter -Applies physical generative 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 physical generative 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 physical generative AI in robot -Describes robust physical generative 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.