Elsevier Adaptive Predefined-Time Attitude Control for Spacecraft (Aerospace Engineering)

Adaptive Predefined-Time Attitude Control for Spacecraft presents the latest advancements in spacecraft control dynamics, with a particular focus on time-bound strategies that guarantee rapid and smooth system stabilization under realistic mission constraints. Rooted in the expertise of scholars with extensive experience in nonlinear and adaptive control, the book establishes a solid theoretical foundation in finite-time and predefined-time formulations before transitioning to sophisticated techniques such as fuzzy logic, dynamic surface control, neural networks, and event-triggered design. Subsequent chapters broaden the scope to encompass multi-spacecraft coordination and time-triggered adaptation, reflecting the growing trend toward autonomy and intelligent systems in modern aerospace applications. Readers are guided through a cohesive suite of state-of-the-art methodologies, along with insights into emerging trends and future frontiers, all engineered to optimize reliability, efficiency, and fault tolerance. Graduate students, early-career researchers, and experienced engineers in both academia and industry will find this volume a comprehensive and indispensable reference for the design and deployment of intelligent attitude control systems in modern flight and satellite missions. Enhances overall spacecraft performance through intelligent control strategies such as neural networks and finite-time control, ensuring robust operation in highly complex and uncertain environments Delivers precise and reliable attitude stabilization using advanced techniques like fixed-time sliding mode control and predefined-time backstepping, maintaining accuracy even in the presence of dynamic external disturbances Ensures fault resilience and mission continuity by employing adaptive and event-triggered control methods that respond proactively to unexpected system failures, preserving functionality without compromising performance Promotes control efficiency and autonomy by integrating real-time decision-making frameworks and low-complexity algorithms that enable spacecraft to adapt to evolving mission conditions with minimal ground intervention