Atsiliepimai
Aprašymas
Apply cybernetic control and AI to autonomous space system design
Autonomous spacecraft operating under extreme communication latency and environmental uncertainty demand robust control, adaptive feedback, and intelligent decision-making. Space Cybernetics: Autonomous Systems and Interplanetary Intelligence applies cybernetic principles to these extraterrestrial challenges, tracing the evolution from early satellite control systems through to autonomous rovers, interplanetary networks, and AI-driven spacecraft design for modern space missions.
Space Cybernetics delivers mathematical tools for orbital dynamics modeling, stochastic uncertainty modeling, and space system control. Coverage extends to quantum entanglement for deep-space communication and AI-human collaboration frameworks for lunar habitats. A companion GitHub repository provides reusable Python and MATLAB scripts, while multiple-choice questions and end-of-chapter problems support structured learning.
Readers will also find:
Designed for graduate students in robotics, aerospace, and control engineering, as well as researchers in space robotics and cybernetics, this book also serves aerospace engineers, policy makers, and private space entrepreneurs seeking rigorous treatment of autonomous systems for extraterrestrial operations.
Apply cybernetic control and AI to autonomous space system design
Autonomous spacecraft operating under extreme communication latency and environmental uncertainty demand robust control, adaptive feedback, and intelligent decision-making. Space Cybernetics: Autonomous Systems and Interplanetary Intelligence applies cybernetic principles to these extraterrestrial challenges, tracing the evolution from early satellite control systems through to autonomous rovers, interplanetary networks, and AI-driven spacecraft design for modern space missions.
Space Cybernetics delivers mathematical tools for orbital dynamics modeling, stochastic uncertainty modeling, and space system control. Coverage extends to quantum entanglement for deep-space communication and AI-human collaboration frameworks for lunar habitats. A companion GitHub repository provides reusable Python and MATLAB scripts, while multiple-choice questions and end-of-chapter problems support structured learning.
Readers will also find:
Designed for graduate students in robotics, aerospace, and control engineering, as well as researchers in space robotics and cybernetics, this book also serves aerospace engineers, policy makers, and private space entrepreneurs seeking rigorous treatment of autonomous systems for extraterrestrial operations.
Atsiliepimai