Earticle

In order to overcome the large power fluctuation under the maximum power point of maximum power point tracking(MPPT) algorithm based on the Perturbation and Observation method(P&O) of traditional solar photovoltaic(SPV), an optimization algorithm based on the three-order difference of power and variable step is presented. In the traditional P&O of MPPT of SPV, the first-order difference of the power is elected as the variation of the power. When the SPV is operated nearby the voltage of maximum power point, the traditional algorithm has its limitation that the power will present the approximate equal amplitude oscillation under the maximum power point because of the false judgment of the algorithm. By analyzing the relationship between the three-order difference of the power and the relative position of the operating point and the maximum power point, the next variation trend of the operating point is presented. The variable step algorithm is applied so the SPV will operate again according to the algorithm based on the three-order difference of power and variable step when the operating point cross the maximum power point first. The correctness and rationality of the proposed algorithm is tested by the results of the Matlab/Simulink.

Wireless sensor networks are set of connections of nodes comprising of several sensor nodes connected to every additional in the course of a wireless environment. Wireless sensor nodes consists of some composite functions such as the detection of signals, collection of signals and data, deviousness and routing of nearby data by implanting them either randomly or by following a specific approach into various areas. In the present paper, the IEEE 802.15.4 protocol was considered which can be used vastly in communication networks. The performance of this protocol was analyzed in this paper through graphical representation. It consists of various useful standards for communication with respect to the wireless sensor network considerations like usage of battery for applications by sensors, the power consumption by various sensors should be low, they provide very extraordinary performance over sensors which works at very short distance and makes it likely to use nearly various frequency bands in the real time applications. The present simulator we had considered was RIVERBED Academic Edition 17.5, which is proficient of producing precise outcomes and gives user a detailed analysis of results which helps in identifying the actual behavior of the real system for real time applications or user designed applications. By using this simulator program, the performance of the network with respect to throughput of the nodes with number of nodes was analyzed which helps in designing a new real time network.

As an important one of recommendation technologies, collaborative filtering algorithms have many advantages, and have been very successful in both research and practice. However they also remain fundamental challenges, such as data sparsity, cold-start, dynamic changes of users’ preferences and interests, and scalability. For purpose of lessening inaccurate recommendations caused by data sparsity, the pre-filled rating matrix is created by introducing a novel similarity computation method to replace the traditional ones. To address the cold-start issue, we propose a hybrid recommendation method that combines collaborative filtering and content-based filtering exploiting the advantages of both methods. To respond positively to dynamic changes of users’ preferences and interests, the improved algorithm takes time factor into consideration as well. Finally we implement parallel execution of the improved algorithm on Hadoop platform, which addresses serious scalability issue when working on big data. The experimental evaluation of our proposed methods took place and the results showed that the improved algorithm has better recommendation quality and real-time performance.

In household heat metering, the user can according to need, through the electromagnetic valve opening and closing frequency to achieve temperature regulation. The heating system is a nonlinear, slow time-varying, lag deposit and other characteristics, usually by fuzzy PID control system. This paper adopts the improved adaptive fuzzy PID control system,through simulation, this scheme improves the robustness of new heating system.

A novel model of stochastic chaotic radar waveform with stochastically stepped carrier frequencies is proposed, in which, a nonlinear system generating an unpredictable aperiodic stochastic chaotic signal (SCS) is used to control stepping of carrier frequencies. The stochastic chaotic frequency-modulation (SCFM) signal is used as the baseband noise signal, which is truly random and has a thumbtack ambiguity function (AF). SCS can be used to estimate velocity and for imaging of high-speed targets. Wideband signal is obtained by coherently synthesizing for high-resolution range (HRR) imaging. Finally, numerical simulations show the effectiveness of the proposed signal model and corresponding algorithms.

This paper proposes a method of automatic exposure that applies image histogram feature (HF) function, which is used under the condition of fast and extensively changing background lighting so as to take automatic exposure control of the high-speed camera. First, multi-spot metering is employed to fetch region of interest from the acquired images and to reduce the calculation amount of systematic metering. Then, by calculating HF function in the region of interest, large step length is selected and exposure time is roughly adjusted. Finally, fuzzy logic is used to calculate the accurately adjusted step length, and threshold limit is applied to search for the optimal exposure time with variable step length, in order to improve the accuracy and the stability of automatic exposure of high-speed cameras. According to the results, within 2ms, the brightness of a one-frame image is measured and exposure time is adjusted. Compared to the conventional automatic exposure methods that are based on the average brightness value, within 0 to 110ms, when light intensity of the light source repeatedly changes between 760lux and 23100lux, the image information entropy obtained by this method is increased by 48.38%, and the variance is reduced by 62.13%. As verified by dynamic experiments, on the premise of ensuring dynamic resolution of the camera, the method in this paper is able to rapidly acquire the optimal exposure time, to provide more favorable and more stable image details, and to offer reference for the subsequent automatic focusing, image recognition and target tracking.

This paper introduces the wind power battery management system design based on the equilibrium technology and the key problems affecting the battery performance, through the analysis of the SOC algorithm, using kalman filter to estimate the SOC, improved to control variables feasibility, provided data for the wind power system dispatcher reference, making the most suitable for the operation of power network dispatching strategy.

This paper, proposed a hybrid strategy for nonlinear control of six degree of freedom (6 DOF) underactuated trirotor Unmanned Aerial Vehicle (UAV). The hybrid control strategy consists of Nonlinear Disturbance Observer (NDO) along with Proportional, Integral and Derivative (PID) controller to control the model of nonlinear (6 DOF) underactuated trirotor UAV. The control model of the UAV is divided in to two sub-models, altitude control and the attitude control such that, the PD controller is used to control the altitude of the UAV and (NDO)with the PID controller is used to control the attitude of UAV. However, the stability of the aircraft is proved by using Lyapunov stability criteria. The robustness of the proposed control strategy is compared with the nonlinear observer design with backstepping control of UAV. It shows that the proposed hybrid strategy have better response less steady state error and good robustness in the presence of continuous disturbance in the model of UAV.