Earticle

In recent years China presents to send power from west to east, and positively develop ultra high voltage and DC transmissions. This paper introduces the DC modeling in high-voltage direct current transmission the general method; respectively analyzed the characteristics of three kinds of simulation model and scope of application. Deduce the mathematical model formula of the main part of DC system, describe the basic control principle. By SIMULINK software to use the detailed model of HVDC system simulation model is established. And in view of the common faults under transient conditions are simulated. Through the simulation results show that in the transient analysis to choose the model is suitable and reliable.

The robust 𝐻∞ control design for bilinear systems with multi inputs is presented in this paper. First, the bilinear system is represented as a dynamic Takagi-Sugeno (TS) fuzzy system by using sector nonlinearity approach. The dynamic TS fuzzy system is a convex combination of local linear systems. The local robust 𝐻∞ controller is designed for each local linear system. The controller synthesis for the local linear systems is then formulated in the bilinear matrix inequalities (BMIs) problem. After that, the BMIs problem is reduced to an equivalent parameter of linear matrix inequalities (LMIs) problem which has a feasible solution. The robust 𝐻∞ controller for bilinear systems as a convex combination of the local robust 𝐻∞ controllers is obtained by using defuzzyfication. The existence condition of the robust 𝐻∞ controller for the bilinear systems is also presented. The simulation results are given to clarify the proposed method for the robust 𝐻∞ control design of the bilinear systems.

A correct understanding of hospital parking characters and parking behavioral regularities is very important to hospital parking planning, making parking management measures and improving the utilization of parking lot. The existing researches in parking behavior concentrate on parking behavior in central area, and the researches on hospital parking behavior are still not deep. Besides, the research methods mainly adopt disaggregate model which only considers driver’s observable manifest variables, neglecting the influence of mental latent variables on the results of parking choice, so the model’s explanatory ability is weakened. Aiming at the hot issue - hospital parking problem, based on the analysis of hospital parking character, this paper puts forward the latent variables of hospital parking mode choice. By improving the utility function of traditional ML disaggregate model, establishing three kinds of SEM-ML integration model which could describe car drivers’ characteristic manifest variables and subjective mental latent variables, and then applying examples to make comparison and analyze. The results show that: Compared with traditional ML model, the SEM-ML model has a better accuracy and explanatory ability. Among the three models, the SEM-ML3 integration model could describe the relationship between latent variables and manifest variables, latent variables and observable variable by structural equation, so it has a better accuracy and explanatory capability. The results validate that manifest variables (parking purpose) and mental latent variables (convenient level and feelings of parking) have effects on hospital parking mode choice. According to the analysis results, this paper proposes corresponding suggestions on planning and managing hospital parking from three aspects: convenience, comfort and safety.

Recently, the production amount of automobile parts is gradually increasing as the market grows and plenty of parts are substituted by plastic products for efficient energy consumption. Thus, systematic control of mass production and management on plastic products is inevitable. Plastic products for the car are manufactured by injection molding process because of the attributes of plastic materials. During injection molding process, defective products can be broken out by internal or external environment change. Currently, most of inspections for the defective products are performed by visual inspection. The authors developed an automatic inspection system that can detect the defects of plastic product using vision system. The authors also developed image processing algorithm in automatic inspection system to detect various type of defects and scratch.

Taking account of the influence of uncertainty, incomplete issues and common cause failure (CCF) to system reliability, a method for reliability analysis based on Dempster-Shafer (D-S) evidence inference and Bayesian network (BN) is proposed by using the advantage of uncertainty reasoning and figurative expression of BN. Firstly, the method to map fault tree into BN with epistemic uncertainty is presented, and the probability of top event (TE) is calculated by belief measure and plausibility measure of evidence. Moreover, by using BN, some useful information can be obtained, through which the weak parts of the system can be identified. The results demonstrate that the proposed method makes a more rational evaluation result, and it is quite valid to deal with uncertainty information in reliability analysis, which provide a reasonable guidance for system fault diagnosis and maintenance and improve the system reliability.

In this paper, as the preliminary step for developing a multi-purpose “Robotic Space” platform to implement advanced technologies easily to realize smart interface to human. We will give an explanation for the Robotic Space system architecture designed and implemented in this study and a short review of existing techniques, since there exists several recent thorough books and review paper on this paper. We will focus on the main results with relevance to the Multi-Sensor Data Fusion with CI of Robotic Space. It is dealt with the general principle of the using the covariance intersection framework to combine mean and covariance estimates without information about their degree of correlation provides a direct solution to the distributed data fusion problem.

Sensor technology has been used in water environment, which comes into being a water environment wireless sensor monitoring network. Monitoring data in the network slowly change, so we propose a geographical energy-efficient multi-hop clustering fusion routing algorithm based on multilayer perceptron (MLP-GEEMHCFR) in this paper to reduce transmittingdata and save the network energy.The algorithm is implemented by initialization phase, stabilization phase and data fusion phase. A multilayer perceptron (MLP) neuronal function model is designed in the data fusion stage using the MLP, and effect of neuron thresholds on the algorithm fusion efficiency is analyzed in detail. The simulation results show that the performance of the MLP-GEEMHCFR is better than a geographical energy-efficient multi-hop clustering routing (GEEMHCR) algorithm without fusion. The data fusion efficiency increases with the neuron threshold.But when the neuron threshold is up to 1 or more, the increasing trend becomesslowly.

To install and debug electrical control equipment is a typical work position for students who major in automation in vocational college. In order to meet the needs of this position, the connection and designation of electrical control lines have become a required part for most of these students. This paper proposes a simple method of automation detection of electrical control circuit based on single chip microcomputer, which is convenient for students to learn by themselves and for teachers to reduce the work pressure in reaching practically. Considering automatic detection of electrical control circuit by single chip microcomputer, the method synthesizes the technology of single chip microcomputer and embedded technology, and codes to construct net lists with nodes through connecting electrical components, so it is a foundation to achieve automatic detection of circuit. Not only is this method economical and practical, but it also helps to gain a good effect in process of teaching.

In this paper, we are integrating clock gating in design of energy efficient equation solver circuits based on Vedic mathematics. Clock gating is one of the best energy efficient techniques. The Sutra 'SunyamSamyasamuccaye' says thatif sum of numerator and sum of denominator is same then we can equate that sum to zero and find the value of unknown variable. In order to test the portability of our design, we are operating our design with respective frequency of different mobile architecture. Operating frequency of iPhone6 is 2100MHz. For thermal analysis of our energy efficient design, we have taken temperatures of four different regions of Furnace Creek Ranch (329.85K), Mohenjo-Daro (326.65K), and median temperature of Delhi (313.15K) and standard normal temperature (294.15K). Saving in clock power dissipation is 96.15% for 1400MHz, 94.59% for 1.2GHz, 93.75% for 2100MHz, 94.23% for 1700MHz, 94.54% for 1800MHz, and 94.02% for 2.2GHz, when we use gated clock instead of un gated one on 40nm FPGA and temperature is 329.85K. Power consumption in 28nm FPGA is less than 40nm FPGA.

The Internet of things is a network that based on the IEEE802.15.4 wireless communication protocol and transmit data between devices. It contains a big variety of communication technology, considering the advantages of low-power,low-cost and large-capacity, ZigBee technology becomes the best way to solve Wireless Personal Area Network portion of Internet of Things. However, due to the theoretic immaturity of this newborn technology and complexity of its hardware implementation, there are numerous problems need to be solved, such as reduce energy consumption to increase the lifetime of zigbee, this paper propose an energy-balanced algorithm which combine and balance ME-AODV(Multipath Energy Aware AODV Routing)and Cluster-Tree routing algorithms. This algorithm employs ME-AODV and Cluster-Tree routing algorithms in different energy conditions to reduce energy consumption and extend the lifetime of network. The simulation have been performed using IEEE802.15.4,ns-2moudule and simulation results show that the improved algorithm can optimize the energy consumption of ZigBee network compared with original algorithm.

Lately, the application of UAV (Unmanned Aerial Vehicle) has drawn increasing attention. However, due to the lack of related systems, safety issues are becoming an urgent matter. The course rollback, a function provided by commercial UAV companies, cannot react to issues about various difficulties and fuel shortage. This is the reason it is necessary to study selecting an emergency landing zone in urgent situations. This study proposes a method for the drone to autonomically select a landing zone in case of an emergency as a model. In the validation stage, Our study analyzes the image according to the procedure and verifies if the site was properly selected. This study has an academic and practical significance as an advanced research on the safe operation of UAV.

Traditionally, the key idea of estimating independent component analysis (ICA) model is to maximize the non-Gaussianity, however, often with the assumption that density of data is near the standardized Gaussian density. To avoid the unsuitable assumption, this article uses the nonparametric density estimating method. A nonparametric independent component analysis algorithm based on Epanechnikov kernel function is proposed in this paper. This algorithm uses the Epanechnikov kernel estimator to estimate random variable distribution, meanwhile, employs the hypothesis test to derive the nonparametric likelihood ratio (NLR) objective function. For optimizing the nonparametric density estimation, the selection of kernel function and bandwidth is crucial. From the perspective of minimizing the mean integrated square error (MISE), this paper discusses the optimal selection and conducts experiments for further study. To increase the algorithmic convergence rate and reduce the running time, the quasi-newton method has been used to optimize the objective function. Compared with previous nonparametric ICA algorithm, the simulation results demonstrate that the proposed method offers better performance both on speech separation and computing capability.

This paper focuses on a sensorless control method for small wind turbines based on permanent magnet synchronous generators. An adaptive intelligent algorithm is proposed to estimate the rotor speed for designing sensorless controllers of small wind turbines. In the proposed algorithm, a model reference adaptive system has been formed by using the instantaneous and steady-state powers to estimate the rotor speed. Then a power speed feedback (PSF) control carries out maximum power point tracking by using the optimum relationship between speed and power, which is kept in a lookup table. The efficiency of the system is improved by vanishing the observation errors and tracking errors. The validity of the proposed algorithm is verified by the simulation results.

The paper describes implementation and application of voltage management system (VMS) to a physical power system for bringing stable and robust operation. The VMS has a role of balancing reactive power generation of the generators, which are controlled by the VMS. The VMS consists of continuous voltage controller (CVC) and discrete voltage controller (DVC). Those are used to maintain the system voltage within stable range. Especially, the CVC induces a supplementary signal to automatic voltage regulator (AVR) to balance reactive power generation of all involved generators. In the paper, the physical application of the VMS is described and the important considerations are introduced. Also, the paper shows the results of the stable application of the VMS.

In recent years, the extensive use of BIM has brought a revolutionary change for the construction industry. As an important technology to support BIM, three-dimensional digital technology has become a hot academic research. The 3D geometric model is the main data expression of modes in BIM environment. But because of the complexity of 3D modeling, the maintenance of the 3D model library in BIM environment will spend a lot of time and cost. The traditional CAD 3D modeling has accumulated a large number of 3D models for the BIM project to reuse. Using the 3D model classification technology can quickly classify the existing 3D model, and save a lot of cost. Deep learning is in recent years a new method of machine learning. In this paper, we use Stacked Auto-Encoders (SAE) to classify 3D models under the environment of BIM. Experiments show that, the method proposed in the paper has achieved good results in the 3D model classification, which provides a new idea for the development of BIM.

This study proposes a systemic method to selecting between two basic types of order picking system picker-to-parts system and put system for different types of customer orders such as wholesaler orders, retailer orders and consumer orders. In essence, order batching and picking area zoning are cluster method about customer order sheet, so the customer order sheet can be gridded into many unit blocks. After the picking time formulation for each system in one-dimensional unit blocks is defined according to the logical movements, the time sequence models for two-dimensional systems are established by filling curves to link the one-dimensional unit blocks to form tow-dimensional system. In consideration of “U” shaped dual tour, the subtraction value between picker-to-parts system and put system is used as the criteria to select the suitable system. Genetic algorithm is adopted to find the optimal value for each system. Through the experimental study, the proposed method is proved to be able to get the suitability of picker-to-parts system and put system for given orders with the hypothetic value of parameters, and some key factors such as zone number, batch size, wave size, dual tour and setup time have significant effect on suitability of each system for different orders.

The adaptive dual control problem of a single-in single-out (SISO) stochastic system with unknown parameters and input delay is studied in this paper. The unknown parameters are assumed to be constant but belong to a known finite set. For each group of possible model parameters, a Kalman filter is used to estimate the system state online and the posterior probability of this model can also be calculated accordingly. The optimal control of each model is designed, based on an M steps ahead loss function. The final dual controller is obtained by a weighted sum of all possible optimal control outputs considering the posterior probabilities of each model. Numerical simulations were performed to verify the effectiveness of the proposed controller.

This paper presents a sliding mode controller based Neural Networks for energy conservation in Induction motor. A Multi layer Neural Network trained by back propagation learning algorithm is used to compensate for the system uncertainties and provide energy efficient operation for a wide range of loads. The trained Neural Network controls the stator voltage for optimal efficiency under all operating conditions. Simulations and experimental studies were performed to establish the suggestion made in this paper. The proposed algorithm was simulated using Matlab/Simulink and the results show that the performance of the control scheme is robust, the chattering problem is solved and efficiency improvement is achieved.

The industrial robot with 6 degree of freedom is studied in this paper. According to the interference problems that exist in the actual cutting process of robot, a method is proposed which could make optimal selection of the trajectory of robot after the interference problems is eliminated. After the determination of the posture of cutting head, the model of intersecting line and programming the cutting trajectory of robot, the 3D model of mechanical arm and incised work piece are imported into OPENGL, using collision detection based on OPENGL to screen the interference point of the robot arm. The cutting trajectory is verified through the simulation with ADAMS. The simulation result shows that the robot can run steadily after eliminating the interference and the intersecting line meets the demands.

More than a few aspects should be taken into consideration when drawing up plans for a traffic light system. If the planners disregard some of these aspects, the traffic light might be not just ineffective, but even more – it might harm the flow of the traffic, might increase the carbon emission and the severest – it might cause vehicle accidents. With the aim of confronting this challenging objective, we suggest in this paper a scheme for a functional intelligent traffic light system model.

The Electric motor coach has become the focus of attention for its energy saving and green non-polluting, but it also poses a new challenge to feedback aspects of steering system and steering feeling. To enhance high-speed handling road sense, this article suggested using genetic algorithm to optimize mixed H2/H∞ system for boosting steering feeling control ability of hydraulic power steering system of electric motor coach based on analyzing electric hydraulic power steering system and feedback torque mathematical model of steering wheel. Simulation result showed that the accumulative error between torque feedback of steering wheel and wheel load torque is obviously reduced after optimization, and the feedback feeling of drivers to road sense has been strengthened.

Due to the popularity of LDPC (Low Density Parity Codes) in modern communication systems, there is a growing need of LDPC encoder with a faster encoding speed and more application compatibility. In this paper, an efficient QC-LDPC encoder architecture is proposed, which is suitable for both IEEE 802.16e standard and IEEE 802.11n standard. Owing to the special structure of multi-diagonal parity matrices, the inverse matrix is replaced with back substitution. Simplified RU algorithm is applied to the encoder structure, and the parallelism is determined by the row number of parity matrices in the two standards. The proposed architecture has full configurability with concern to code rate and code length. Simulation results confirm that the encoders work successfully from 1/2 rate to 5/6 rate under both two standards. To validate its feasibility, we have tested all code lengths of IEEE 802.11n standard and IEEE 806.12e standard. They all work accurately with the proposed encoder architecture, with the output throughputs ranging between 538 Mbps and 2879 Mbps.

In this work , Csf/SiC composite was hot pressed by adding short carbon fiber and nano carbon black and nano SiC powder into SiC powder by rapid hot press sintering in order to improve the fracture toughness and other mechanical properties .The density, hardness, phase composition, mechanical properties of Csf/SiC composite were studied, the toughening principle was also discussed. The results indicated that: the Csf/SiC composite had a high density of above 98% in less than 30vol.% short carbon fiber . The hardness was decreased with the increase of the amount of Csf fibe. The composite were mainly composed of 6H-SiC and C, the high temperature graphitization of short carbon fiber resulted the diffraction peaks of C in crystalline by XRD. Short carbon fibers were distributed uniformly and no aggregation in the matrix when contents of fiber were less 30vol.% by SEM test. The bending strength of the composite reached 423MPa at optimal conditions. Too many fibers in the matrix led to decline of bending strength sharply. The fracture toughness reached 4.9MPa·m1/2 of maximum with more obvious toughening effect. The debonding, pullout and breakage behaviors of the Csf fiber and crack propagation were identified as the dominant toughing mechanism in such composites.

The problem of gait planning for the quadruped search robot is described as an uncertainty discrete system. According to the basic gait elements of the quadruped search robot, the periodic gait of the robot is analyzed on the basis of gait timing diagram. The non-fragile control theory is proposed for gait planning control of quadruped search robot. A non-fragile reliable adaptive controller is designed for adaptive gait transition with the D-stability, which makes the gait planning to be regular, causal and D-stable. The condition of controller is given based on robust control theory, which include theorem 1 and theorem 2. And the approaches of designing the controller are given in terms of linear matrix inequalities. The results given by linear matrix inequalities indicate that the proposed non-fragile reliable robust controller is correct and effective.

In order to reduce the power consumption, and enhance the drive ability of robot, the PMSM is adopted in the drive system of patrol robot. The PMSM need a more efficient and cheaper drive system of patrol robot. The hardware platform of drive system of patrol robot based on the MC9S12XS128 is designed, the three-phase inverter is set up based on the BTS7960, PMSM is controlled by vector control algorithm, the three closed-loop control of position, velocity and current is realized. The experiment shows that actual current of axis q traces the setting value fast, and dynamic response of velocity is fast, and the trace of velocity in the steady state is stable, and the position loop is stable.

Parallel operation of Multi-inverter can greatly improve the system's flexibility , power system's Capacity, redundancy and reliability, current through the power switch is divided, so the current stress for power switch can also be greatly reduced, the performance is improved with costs effective and power density. The conventional droop-control strategy which is adopted generally for parallel inverter regulates the phase and the amplitude of the output voltage according to output active power and reactive power，respectively.And active power and reactive power are related to both output amplitude and output phase for double closed-loop feedback voltage—source inverter．The control method of the droop control with virtual impedance is applied in this paper. The PQ droop control strategy for parallel single phase inverter is illustrated. PQ droop control scheme can effectively stabilize the droop control system to automatically exit, and also can achieve the expected load-sharing flow effect. Droop control without mutual connection, the inverter can be conveniently connected and removed. Finally， simulation results by obtained MATLAB / Simulink software is given to verify the effectiveness of theoretical analysis .

The basic structure of the electromagnetic induction type voltage transformer is the core and primary, secondary winding. Characteristics of capacity are small and relatively constant. This paper introduces the application of electric energy meter, including two kinds of three-phase electric energy meter (three-phase two elements and three element phase) and non reactive energy meter. In this paper, the high voltage electric energy metering system of fault conditions is analyzed. The paper presents novel method of high voltage power metering circuit fault detection based on Electric energy meter phase and voltage transformer. The voltage circuit fault that electric energy meter pressure loss, less pressure fault detection method is analyzed.