This paper proposes an adaptive incremental nonlinear dynamic inversion (INDI) controller for unmanned aerial manipulators (UAMs). A novel adaptive law is employed to enable aerial manipulators to manage the inertia parameter changes that occur when the manipulator moves or picks up unknown objects during any phase of the UAM’s flight maneuver. The adaptive law utilizes a Kalman filter to estimate a set of weighting factors employed to adjust the control gain matrix of a previously developed INDI control law formulated for the corresponding UAV (no manipulator included). The proposed adaptive control scheme uses acceleration and actuator input measurements of the UAV without necessitating any knowledge about the manipulator, its movements, or the objects being grasped, thus enabling the use of previously developed INDI UAV controllers for UAMs. The algorithm is validated through simulations demonstrating that the adaptive control gain matrix used in the UAV’s INDI controller is promptly updated based on the UAM maneuvers, resulting in effective UAV and robot arm control.

This paper introduces an adaptive Incremental Nonlinear Dynamic Inversion (INDI) control methodology with guaranteed stability for a highly maneuverable unmanned aerial manipulator (UAM) designed to operate under demanding conditions, such as rapid arm movements and varying manipulated payloads. This work extends previous work on the control of aerial manipulators by addressing control effectiveness uncertainties. The stability bounds of the inertia matrix within the control effectiveness matrix are derived through a detailed eigenvalue analysis, ensuring that the eigenvalues consistently remain within a specified stability threshold. The proposed methodology ensures both stability and control responsiveness by dynamically adjusting the inertia parameters of the control effectiveness matrix within stability-guaranteeing limits. The methodology is validated through extensive simulation tests showing that the proposed adaptive INDI controller outperforms previous UAM controllers, effectively coping with disturbances caused by varying grasped payloads/masses and extended arm movements with guaranteed stability.

This paper introduces a novel position and attitude trajectory tracking control law for unmanned aerial manipulators (UAMs) with aerobatic flight capabilities, enabling them to perform complex aerial manipulation tasks with objects of unknown inertia parameters. The proposed control law is structured in a cascaded form, with control gains selected through frequency analysis based on a previously developed adaptive incremental nonlinear dynamic inversion (INDI) controller. A quaternion representation is used to avoid singularity issues in attitude control during unmanned aerial vehicle flight maneuvers and simultaneous arm manipulation. The methodology is validated through extensive simulations, demonstrating that the control law enables the UAM to perform static and dynamic pitch-hovering motions while effectively compensating for disturbances and inertia variations induced by the manipulator as it moves the object in midair.

This paper presents a novel trajectory tracking control law for Unmanned Aerial Manipulators (UAMs), enabling hovering at nonzero pitch angles while manipulating objects with unknown inertia. The cascaded control structure leverages frequency analysis for gain selection, building on an adaptive Incremental Nonlinear Dynamic Inversion (INDI) controller. Quaternion-based attitude control ensures singularity-free operation throughout flight and manipulation. Extensive simulations validate the approach, demonstrating stable pitch-hovering and effective disturbance compensation during dynamic object handling.