Trajectory Tracking Control Design for Autonomous Helicopters with Guaranteed Error Bounds
This work provides certified buffer zones for upper-level trajectory planning for autonomous helicopters, which is crucial for safety-critical applications.
This paper develops a framework to compute formally guaranteed trajectory tracking error bounds for autonomous helicopters using Robust Positive Invariant (RPI) sets. The method establishes closed-loop translational error dynamics as a polytopic linear parameter-varying form, from which ellipsoidal RPI sets provide explicit position error bounds.
This paper presents a systematic framework for computing formally guaranteed trajectory tracking error bounds for autonomous helicopters based on Robust Positive Invariant (RPI) sets. The approach focuses on establishing a closed-loop translational error dynamics which is cast into polytopic linear parameter-varying form with bounded additive and state-dependent disturbances. Ellipsoidal RPI sets are computed, yielding explicit position error bounds suitable as certified buffer zones in upper-level trajectory planning. Three controller architectures are compared with respect to the conservatism of their error bounds and tracking performance. Simulation results on a nonlinear helicopter model demonstrate that all architectures respect the derived bounds, while highlighting trade-offs between dynamical fidelity and conservatism in invariant set computation.