Robustifying Payload Carrying Operations for Quadrotors Under Time-Varying State Constraints and Uncertainty

Quadrotors find a vast potential use in delivery and disaster relief operations. Control becomes critical in such scenarios, especially when quadrotors have to manoeuvre through constrained spaces or deliver payloads at precise locations in the presence of external disturbances and parametric uncertainties stemming from uncertain payloads. Therefore, the controller has to
guarantee a predefined tracking accuracy not to violate the state constraints
. On the other hand, conventional fixed-valued state constraints are not suitable in many scenarios such as (i) initial offset being well beyond the expected accuracy, (ii) system dynamics experiencing significant transients due to the dropping of the payload. However, to the best of the authors’ knowledge, state-of-the-art controllers do not provide any solution for an underactuated system like a quadrotor when the system needs to honour time-varying constraints under uncertainties. This work proposes a controller for quadrotors which is robust against external disturbances and parametric variations and guarantees a time-varying predefined position, velocity, attitude, and attitude-rate accuracy. The closed-loop system stability is established analytically, and the effectiveness of the proposed controller is validated experimentally compared to the state-of-the-art under a precision payload delivery scenario.