Hierarchical POMDP-Based Cooperative Search and Adaptive Attitude Control Strategy for Multi-UAV Systems

To address the coupled problem of cooperative search and attitude control faced by multi-UAV systems in complex uncertain environments, a unified control strategy based on hierarchical POMDP is proposed. This strategy effectively decomposes multi-scale decision-making problems by constructing a hierarchical architecture of upper-level task planning and lower-level attitude control. The upper level employs an information-entropy-maximization search algorithm that integrates auction-based task allocation, weighted Voronoi region partitioning, and an improved RRT path planner. The lower level designs an adaptive attitude controller based on the POMDP framework, employing particle filtering for parameter estimation and combining projection adaptive laws with fuzzy logic compensation mechanisms to handle model uncertainties and external disturbances. Simulation experiments demonstrate that compared to traditional methods, the proposed strategy achieves improvements of 32.5%, 45.8%, and maintains over 70% performance in search time, attitude control accuracy, and system robustness, respectively. This method provides a new theoretical framework and technical approach for efficient cooperation of multi-UAV systems in complex task scenarios.