- ホーム
- > 洋書
- > 英文書
- > Science / Mathematics
Full Description
The Control of Multiple Unmanned Aerial Vehicles: Synthesis, Functionalization to Applications provides readers with a unified framework to address the challenges of multi-UAV target encirclement tracking control. This is achieved by comprehensively integrating the concepts of dynamic modelling, state and disturbance estimation, guidance law design, distributed control, obstacle avoidance and reinforcement learning-based formation tracking control with multi-UAV encirclement tracking systems. The book provides practical insight and solutions to the challenges of multi-UAV use, including limited sensing, communication constraint, wind disturbances and obstacle and collision avoidance, enabling readers to effectively apply the concepts to their work or research. Cutting-edge control techniques and advanced theories are explored, including robust distributed control, adaptive neural network approximation, reinforcement learning and multi-agent systems, presenting readers with state-of-the-art methodologies from which to develop practical applications of UAV formation. Each guidance and control method presented in the book is accompanied by a thorough comprehensive analysis to ensure that each is theoretically grounded. The book ensures transparency by providing open-access simulation codes, allowing readers to easily access and reproduce presented results.
Contents
1. Abstract
2. UAV Modeling
3. Distributed Control of Target Cooperative Encirclement and Tracking Using Range-Based Measurements
4. Target Localization and Encirclement Control for Multi-UAVs with Limited Information
5. Distributed Robust Formation Tracking Control for Multi-UAV Systems
6. Finite-Time Encirclement Control of Moving Target Tracking for UAV Formation
7. Fixed-Time Encirclement Control of Moving Target Tracking for UAV Formation
8. Predefined-Time Control for Multi-Targets Encirclement and Tracking for UAV Formation
9. Reinforcement Learning-based Multi-UAVs Formation Tracking Control
10. Conclusions and Future Directions
