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:

• Detailed treatment of adaptive feedback mechanisms enabling autonomous decision-making in spacecraft operating beyond real-time ground control range
• Analysis of interplanetary network architectures and communication protocols designed to function reliably under extreme signal propagation delays
• Exploration of satellite operations management using cybernetic control loops for maintaining stability and performance in orbital environments
• Historical context connecting Norbert Wiener's foundational cybernetics concepts to contemporary autonomous rover and spacecraft system design
• Supplementary instructor materials including question banks and code repositories designed to support graduate-level courses in space systems engineering

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.

Kelvin Kian Loong Wong, PhD, is a distinguished researcher in computational science and medical image processing who coined the term "Cybernetical Intelligence" and is the inventor and founder of Deep Red AI. A Senior Member of the IEEE, he has been at the forefront of merging cybernetics and artificial intelligence, with degrees from Nanyang Technological University, The University of Sydney, and a PhD from The University of Adelaide.

Andrew W. H. Ip, PhD, is a Senior Research Fellow in the Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University, and Professor Emeritus and Adjunct Professor of Mechanical Engineering at the University of Saskatchewan, Canada. With over 30 years of experience spanning academia, research, industry, and consultancy, he earned his PhD from Loughborough University, UK, and is a Senior Member of IEEE.