This brief presents a new trajectory generation and an effective antisway tracking control (ATC) method for a multirotor unmanned aerial vehicle (UAV) with a cable-suspended payload. The UAV transportation system has been developed due to its ability to easily deliver small packages. However, existing methods lack research on transient response accompanied by aggressive rotation of the UAV and inevitable payload swing. Unfortunately, these motions become intensified when the input is dynamically unfeasible, such as step-like changes. Trajectory generation to minimize the swing motion provides a dynamically feasible trajectory between waypoints. The proposed method provides fast settling time with remarkably little payload swing. In addition, the ATC is developed on the basis of linear-quadratic (LQ) control to deal with motion coupling issues. A payload state estimator is also designed that requires no sensor for the payload. Finally, the performance of the proposed method is verified by numerical simulation and experimental results that show the possibility of safe and fast transportation with a minimal swing.

This paper presents to develop a fault-tolerant control (FTC) to cope with defective thrust systems in multirotor unmanned aerial vehicles (UAV). Faults can occur for a number of reasons in flight, including defective motor performance and damaged propellers. The faults deform both the thrust and torque outputs that could result in the UAV crashing and causing secondary accidents. The FTC method in the paper is developed to reconfigure thrust systems using the optimal control when significant degrees of failure occurs in a number of defective motors. Orientation control could be abandoned to maintain the controllability of altitude when the control output loss cannot be compensated for because of motor saturation. Specifically, yaw motion control is sacrificed, resulting in a rapid rotation and divergence of position control. The divergence can be resolved by a feed forward control loop on the roll and pitch angles. Both simulations and experiments are implemented to demonstrate the performance of the FTC. The results indicate that the proposed FTC can be implemented to minimize accidents from failures of main thrust systems.

A theory of coupled characteristic modes is developed for computing the eigenmodes of a coupled array using the modes of the isolated elements and the corresponding mutual interaction matrix. The systematic blending of the matrix block partitioning method and the orthogonal properties of the eigenvectors provide a generalized formulation considering the interaction of all the isolated modes. Later, closed-form solutions have been derived for the dominant coupled modes with the assumption of one-to-one mode coupling of the isolated elements. The idea has been further extended for two-to-two mode interaction modeling which conforms into a fourth-order generalized characteristic equation. The higher-order extension can be solved in a similar numerical process. Different examples have been considered to validate the proposed technique.

This article presents a robust predictor-based sliding-mode control (RPSMC) for multirotor unmanned aerial vehicles (UAVs) to ensure desired tracking control under time delays, which appear in practice by communications, complex computation, and actuator delays. Many UAV applications have difficulty in control and operation due to various types of time delays, resulting in repeated commands, severe control instability, and then mission failure. However, existing controllers have limitations in solving time delay problems. In this article, the RPSMC with the prediction of future disturbance and reference trajectory is developed for the multirotor UAV to minimize the effects of time delay, robustly deal with external disturbances, and further achieve desired tracking control. The performance of RPSMC for the multirotor UAV is verified under various time delays and disturbances in numerical simulations. The results show the robustness and fast control convergence compared with proportional-integral-differential and conventional predictor-based controllers. Experimental results with step response and tracking of circular trajectory demonstrate the feasibility and performance of the RPSMC for UAVs in the presence of various time delays and disturbances.