Abstract
The use of Fourier methods in wave-front reconstruction can significantly reduce the computation time for large telescopes with a high number of degrees of freedom. However, Fourier algorithms for discrete data require a rectangular data set which conform to specific boundary requirements, whereas wave-front sensor data is typically defined over a circular domain (the telescope pupil). Here we present an iterative Gerchberg routine modified for the purposes of discrete wave-front reconstruction which adapts the measurement data (wave-front sensor slopes) for Fourier analysis, fulfilling the requirements of the fast Fourier transform (FFT) and providing accurate reconstruction. The routine is used in the adaptation step only and can be coupled to any other Wiener-like or least-squares method. We compare simulations using this method with previous Fourier methods and show an increase in performance in terms of Strehl ratio and a reduction in noise propagation for a 40x40 SPHERE-like adaptive optics system. For closed loop operation with minimal iterations the Gerchberg method provides an improvement in Strehl, from 95.4% to 96.9% in K-band. This corresponds to ~ 40 nm improvement in rms, and avoids the high spatial frequency errors present in other methods, providing an increase in contrast towards the edge of the correctable band.

Abstract
The penetration of micro-generation brings complex problems to the energy field. In this way, various simulators were designed to give decision support for the stakeholders, however, they intent to solve very specific problems. The proposed tool enables the interoperability between heterogeneous simulators, to simulate more complex problems.

Abstract
This paper introduces a novel control design method for stabilization of input constrained non-holonomic wheeled systems. Important classes of mobile robots can be controlled by the proposed method, namely differential drive robots and car like systems where certain constraints are imposed on the system inputs and states. The proposed control is based on the recently developed Constrained Directions Method (CDM). CDM guarantees stabilization and preservation of the constraints on the inputs and provides control over the transient performance of robot. Moreover, it has been shown that CDM has a built-in preventive measure against wheel slip due to the inverse proportionality of robot forward velocity to the curvature of the path. Simulation results are used to show the validity of the proposed stabilizing control and to compare the performance of CDM with several well-known methods from the literature.

Abstract
Objectives - This study aimed to identify: (i) the most relevant chronic diseases in terms of the application of technologies for ageing in place to promote the empowerment of patients; and (ii) types, outcomes and impacts of technologies for ageing in place being used to promote the empowerment of patients with chronic diseases. Methods - A systematic review of reviews and meta-analysis was performed based on a search of the literature. Results - A total of 34 reviews and meta-analysis across several chronic diseases were retrieved. These studies compare the empowerment of patients supported by different technologies with usual care. Conclusion - Technologies for ageing in place have positive effects on various health related outcomes, but further research is required to allow their incorporation in the clinical practice. © Springer International Publishing AG 2017.

Abstract
In this paper we address the allocation of perception tasks among a set of multiple robots, for tasks such as inspection, surveillance, or search in structured environments. We consider a set of target regions of interest in a mapped environment that need to be sensed by any of the robots, and the problem is to find paths for the robots that cover all the target regions with minimal cost. We consider not only sensing range when determining paths for the robots to perceive the targets, but also a sensor cost function that can be adapted to each robot’s sensor. Thus the planning has to search for paths with minimal motion and perception cost, instead of the traditional approach where line-of-sight is the only requirement in a motion cost minimization problem. Our contribution is to use planning to determine possible perception positions for every robot, which we cluster and then use as possible waypoints that can be used to construct paths for all the robots. Given the combinatorial characteristics of path determination in this setting, we contribute a construction heuristic to find paths that guarantee full coverage of all the feasible perception target regions, while minimizing the overall cost. We assume robots are heterogeneous regarding their geometric properties, such as size and maximum perception range. We consider simulated scenarios where we show the benefits of our approach, enabling multi-robot path planning for perception of multiple regions of interest.

Abstract
To address the static voltage stability issue and suppress the voltage fluctuation caused by the increasing integration of wind farms and solar photovoltaic (PV) power plants, a two-tier reactive power and voltage control strategy based on ARMA power forecasting models for wind and solar plants is proposed in this paper. Firstly, ARMA models are established to forecast the output of wind farms and solar PV plants. Secondly, the discrete equipment is pre-regulated based on the single-step prediction information from ARMA forecasting models according to the optimization result. Thirdly, a multi-objective optimization model is presented and solved by particle swarm optimization (PSO) according to the measured data and the proposed static voltage stability index. Finally, the IEEE14 bus system including a wind farm and solar PV plant is utilized to test the effectiveness of the proposed strategy. The results show that the proposed strategy can suppress voltage fluctuation and improve the static voltage stability under the condition of high penetration of renewables including wind and solar power.