Developing methods for autonomous landing of an unmanned aerial vehicle (UAV) on a mobile platform has been an active area of research over the past decade, as it offers an attractive solution for cases where rapid deployment and recovery of a fleet of UAVs, continuous flight tasks, extended operational ranges, and mobile recharging stations are desired. In this work, we present a new autonomous landing method that can be implemented on micro UAVs that require high-bandwidth feedback control loops for safe landing under various uncertainties and wind disturbances. We present our system architecture, including dynamic modeling of the UAV with a gimbaled camera, implementation of a Kalman filter for optimal localization of the mobile platform, and development of model predictive control (MPC), for guidance of UAVs. We demonstrate autonomous landing with an error of less than 37 cm from the center of a mobile platform traveling at a speed of up to 12 m/s under the condition of noisy measurements and wind disturbances.

The estimation of unknown inputs and/or disturbances has been a topic of constant interest in control engineering for the past several decades; see [1] for a detailed survey on the development of unknown input observers. Disturbance observers (DOBs) are a special class of unknown input observers that were introduced for robust motion-control applications in the early 1980s [2]. Since their introduction in the literature, DOBs have been employed efficaciously in numerous robust control and fault-detection applications, including process control [3], [4] and mechatronics [5]-[9]. Figure 1 depicts a DOB employed in a typical control system. The DOB is used to reconstruct, from the measured output variables and the known control inputs applied to the system, unknown disturbances that are acting on the plant. The output of the DOB, namely, the estimated disturbance, can then be used in feedforward compensation of disturbances or faults.

This paper investigates the problem of maneuvering control for planar snake robots. The control objective is to make the center of mass of the snake robot converge to a desired path and traverse the path with a desired velocity. The proposed feedback control strategy enforces virtual constraints encoding a lateral undulatory gait, parametrized by the states of dynamic compensators used to regulate the orientation and forward speed of the snake robot.

Teleoperation systems are subject to different types of disturbances. Such disturbances, when unaccounted for, may cause poor performance and even instability of the teleoperation system. This study presents a novel non-linear bilateral control scheme using the concept of ‘disturbance observer-based control’ for non-linear teleoperation systems. Lumping the effects of dynamic uncertainties and external disturbances into a single disturbance term enables us to design a disturbance observer to suppress these disturbances and alleviate their adverse effects on the teleoperation system. A disturbance observer-based control law is proposed for non-linear teleoperation systems which will guarantee global asymptotic force tracking and global exponential position and disturbance tracking when the bilateral teleoperation system is experiencing slow-varying disturbances. In the case of fast-varying disturbances, the tracking errors are shown to be globally uniformly ultimately bounded, with an ultimate bound that can be made as small as desired using the design parameters. Simulations are presented to show the effectiveness of the proposed approach.