The incorporation of wind energy as a non-conventional energy source has received a lot of attention. The selection of wind turbine (WT) prototypes and their installation based on assessment and analysis is considered as a major problem. This paper focuses on addressing the aforementioned issues through a Weibull distribution technique based on five different methods. The accurate results are obtained by considering the real-time data of a particular site located in the coastal zone of Pakistan. Based on the computations, it is observed that the proposed site has most suitable wind characteristics, low turbulence intensity, wind shear exponent located in a safe region, adequate generation with the most adequate capacity factor and wind potential. The wind potential of the proposed site is explicitly evaluated with the support of wind rose diagrams at different heights. The energy generated by ten different prototypes will suggest the most optimum and implausible WT models. Correspondingly, the most capricious as well as optimal methods are also classified among the five Weibull parameters. Moreover, this study provides a meaningful course of action for the selection of a suitable site, WT prototype and parameters evaluation based on the real-time data for powering local communities.

An adaptive neural observer design is presented for the nonlinear quadrotor unmanned aerial vehicle (UAV). This proposed observer design is motivated by the practical quadrotor where the whole dynamical model of system is unavailable. In this paper, dynamics of the quadrotor UAV system and its state space model are discussed and a neural observer design, using a back propagation algorithm is presented. The steady state error is reduced with the neural network term in the estimator design and the transient performance of the system is improved. This proposed methodology reduces the number of sensors and weight of the quadrotor which results in the decrease of manufacturing cost. A Lyapunov-based stability analysis is utilized to prove the convergence of error to the neighborhood of zero. The performance and capabilities of the design procedure are demonstrated by the Simulation results.