Ocean waves are a huge, largely untapped energy resource, and the potential for extracting energy from waves is considerable. Research in this area is driven by the need to meet renewable energy targets, but is relatively immature compared to other renewable energy technologies. This review introduces the general status of wave energy and evaluates the device types that represent current wave energy converter (WEC) technology, particularly focusing on work being undertaken within the United Kingdom. The possible power take-off systems are identified, followed by a consideration of some of the control strategies to enhance the efficiency of point absorber-type WECs. There is a lack of convergence on the best method of extracting energy from the waves and, although previous innovation has generally focused on the concept and design of the primary interface, questions arise concerning how best to optimize the powertrain. This article concludes with some suggestions of future developments.

Rotary-wing unmanned aerial vehicles (UAVs) have the ability to operate in confined spaces and to hover over point of interest, but they have limited flight time and endurance. Conventional contact-based charging system for UAVs has been used, but it requires high landing accuracy for proper docking. Instead of the conventional system, autonomous wireless battery charging system for UAVs in outdoor conditions is proposed in this paper. UAVs can be wirelessly charged using the proposed charging system, regardless of yaw angle between UAVs and wireless charging pad, which can further reduce their control complexity for autonomous landing. The increased overall mission time eventually relaxes the limitations on payload and flight time. In this paper, a cost effective automatic recharging solution for UAVs in outdoor environments is proposed using wireless power transfer (WPT). This research proposes a global positioning system (GPS) and vision-based closed-loop target detection and a tracking system for precise landing of quadcopters in outdoor environments. The system uses the onboard camera to detect the shape, color and position of the defined target in image frame. Based on the offset of the target from the center of the image frame, control commands are generated to track and maintain the center position. Commercially available AR.Drone. was used to demonstrate the proposed concept which is equppied with bottom camera and GPS. Experiments and analyses showed good performance, and about 75% average WPT efficiency was achieved in this research.

The unique musculoskeletal structure of the human hand brings in wider dexterous capabilities to grasp and manipulate a repertoire of objects than the non-human primates. It has been widely accepted that the orientation and the position of the thumb plays an important role in this characteristic behavior. There have been numerous attempts to develop anthropomorphic robotic hands with varying levels of success. Nevertheless, manipulation ability in those hands is to be ameliorated even though they can grasp objects successfully. An appropriate model of the thumb is important to manipulate the objects against the fingers and to maintain the stability. Modeling these complex interactions about the mechanical axes of the joints and how to incorporate these joints in robotic thumbs is a challenging task. This paper presents a review of the biomechanics of the human thumb and the robotic thumb designs to identify opportunities for future anthropomorphic robotic hands.

This paper presents a computationally fast and efficient least-squares method to minimize the vibration of any general rotor-bearing system by the application of external control forces. The D-optimality concept is used to optimize the force locations. The proposed method provides a wide range of statistical information, and the sensitivity of the optimum response to changes in the control forces. Magnetic bearings can be applied to implement the open-loop adaptive vibration control strategies outlined in the paper. These components can also be used to inject a multi-frequency test signal as required for identi­fication studies.

We introduce an adaptive variable bias current control scheme to minimize the energy consumption of magnetic bearings without altering the dynamic performance. We developed analytical expressions for the optimum bias current settings for both differential and unidirectional modes of operation as a function of the orbit size and the desired bearing stiffness. The orbit size is measured in situ by a recursive Fourier coefficient calculation. The analytical results are presented in normalized variables, and hence can be applied to any size and type of magnetic bearing. Both zero and nonzero static load cases are considered. We show analytically that, under variable bias current operation, the differential mode provides better energy efficiency and stiffness capacity than the unidirectional mode. We present the energy consumption data obtained experimentally on a flexible rotor magnetic bearing rig. The data show that, with the proposed variable bias current approach, a significant energy saving can be obtained without deterioration of dynamic performance

Active magnetic bearings (AMBs) offer contact-free and frictionless support of rotating machinery. However, because of their limited force capacity, they have to incorporate retainer bearings to protect the rotor and stator laminations against high-amplitude vibration levels. Efficient modeling of contact dynamics is important for the design of adaptive controllers to prevent contact. If, however, contact does occur, it is necessary to recover the rotor position with minimum damage and without shutting down the system. This paper utilizes constrained Lagrangian equations of motion to develop a computationally efficient method to model contact dynamics. The method does not require a direct physical modeling of contact forces, although the contact forces are automatically evaluated from the constraint conditions, and it can be applied to multicontact cases. Furthermore, the technique is capable of detecting and simulating the destructive backward whirl rolling motion. A model reduction technique is introduced to improve the computational efficiency. This is demonstrated by comparing numerical predictions with experimental results, obtained for a 2-m-long flexible rotor supported by two magnetic bearings