Adaptive Output Feedback Trajectory Tracking Control of an Indoor Blimp: Controller Design and Experiment Validation

Due to its safety and the flight duration, the indoor blimp robot is an ideal choice for cruise monitoring and inspection. In this article, the robust trajectory tracking problem for a helium-filled blimp is investigated to enhance its adaptability within indoor environments. Specifically, the echo state network (ESN) is employed to estimate the external disturbances and parameter uncertainties experienced by the blimp. To address the issue of unreliable measured velocities, an ESN-based state observer which uses output feedback signals is designed to estimate velocities. Moreover, a tan-type asymmetric barrier Lyapunov function (BLF) is proposed to cope with the time-varying error constraints. All signals in the closed-loop system are proven to be globally ultimately uniformly bounded through Lyapunov techniques. Finally, a series of hardware experiments are conducted on a self-built indoor blimp platform, which demonstrates the effectiveness of the proposed trajectory tracking control scheme.