Improved Learning Observer-Based Robust Formation Tracking Control of Helicopters Under Fixed and Switching Topologies

This paper presents a distributed-centralized control strategy for the formation control of small-scale unmanned he licopters under model uncertainty and external disturbances. The control framework is based upon a dynamic model decomposed into strongly coupled position and attitude subsystems. For the position subsystem, a topological sliding mode controller is designed to utilize the communication network for formation tracking, while a barrier function is incorporated into the attitude subsystem to guarantee synchronization within a predetermined range. In order to enhance the robustness, an improved learning observer is introduced to estimate and compensate for the composite disturbances in real time. The stability of the closed-loop system is proved by using the Lyapunov framework. Comprehensive numerical simulations are conducted to verify the effectiveness and robustness of the proposed strategy under both fixed and switching communication topologies. The results demonstrate the proposed control method can maintain the stable operation of the helicopter formation even under the combined effects of continuous disturbances and dynamic network changes.