无刷直流电机的无位置传感器DSP控制

本文介绍了无刷直流电机的DSP控制,详细介绍了在无刷直流电机控制中反电势检测换相的原理;反电势、电流检测的管理;以及反电势检测相位的软件法实时修正。并介绍了基于DSP的无刷直流电机的控制算法及其启动运行控制过程。

基于无线传感器网络定位技术的图书馆智能管理创新

"互联网+"时代,信息技术的发展对图书馆的智能化管理工作提出了更高的要求。文章概述了无线传感器网络与定位技术,重点讨论了如何将WSN定位技术运用到图书智能管理,通过定位技术与大数据、云计算等信息技术的结合,推动图书馆智能系统建设和智能化发展。

Anti-reverse rotation startup method for sensorless brushless DC motor

In order to start up the brushless DC motor （BLDCM） without reverse rotation and smoothly switch the running state of the motor, a novel startup and smoothly switching method for a sensodess BLDCM is presented. Based on the saturation effect of the stator iron, six short voltage pulses are applied to determine the initial rotor position and the rotor can be found within 60°. After that, a series of short and long voltage pulses are used to accelerate the motor and the variation of the response current is utilized to detect the rotor position dynamically. When the motor reaches a certain speed at which the back-electromotive force （EMF） method can be applied, all the power devices are turned off and the running state of the motor is smoothly switched at the moment determined by the relationship between the terminal voltage waveform and the commutation phases. The experimental results verify the feasibility and validity of the proposed method.

同步旋转坐标系下新型滑模观测器算法的研究

针对基于永磁同步电机(PMSM)滑模观测器无位置传感器抖动问题,采用锁相环估计同步电机转子位置和速度,将滑模观测器(SMO)感应电势和锁相环(PLL)结合一体。新型滑模观测器算法能减少转子位置、转速估算误差和复杂度。最后,利用MATLAB仿真对同步坐标系下新型滑模观测器算法进行验证,实验结果表明新型滑模观测器算法对比传统滑模观测器在一定程度上能抑制抖动,动态与控制性能均有所提高。

Improved estimation of rotor position for sensorless control of a PMSM based on a sliding mode observer

This work proposes a new strategy to improve the rotor position estimation of a permanent magnet synchronous motor(PMSM) over wide speed range. Rotor position estimation of a PMSM is performed by using sliding mode observer(SMO). An adaptive observer gain was designed based on Lyapunov function and applied to solve the chattering problem caused by the discontinuous function of the SMO in the wide speed range. The cascade low-pass filter(LPF) with variable cut-off frequency was proposed to reduce the chattering problem and to attenuate the filtering capability of the SMO. In addition, the phase shift caused by the filter was counterbalanced by applying the variable phase delay compensation for the whole speed area. High accuracy estimation result of the rotor position was obtained in the experiment by applying the proposed estimation strategy.

NBP-based localization algorithm for wireless sensor networks in NLOS environments

To mitigate the impacts of non-line-of-sight（NLOS） errors on location accuracy, a non-parametric belief propagation（NBP）-based localization algorithm in the NLOS environment for wireless sensor networks is proposed.According to the amount of prior information known about the probabilities and distribution parameters of the NLOS error distribution, three different cases of the maximum a posterior（MAP） localization problems are introduced. The first case is the idealized case, i. e., the range measurements in the NLOS conditions and the corresponding distribution parameters of the NLOS errors are known. The probability of a communication of a pair of nodes in the NLOS conditions and the corresponding distribution parameters of the NLOS errors are known in the second case. The third case is the worst case, in which only knowledge about noise measurement power is obtained. The proposed algorithm is compared with the maximum likelihood-simulated annealing（ML-SA）-based localization algorithm. Simulation results demonstrate that the proposed algorithm provides good location accuracy and considerably outperforms the ML-SA-based localization algorithm for every case. The root mean square error（RMSE）of the location estimate of the NBP-based localization algorithm is reduced by about 1. 6 m in Case 1, 1. 8 m in Case 2 and 2. 3 m in Case 3 compared with the ML-SA-based localization algorithm. Therefore, in the NLOS environments,the localization algorithms can obtain the location estimates with high accuracy by using the NBP method.

Multiple k-hop clusters based routing scheme to preserve source-location privacy in WSNs

Privacy is becoming one of the most notable challenges threatening wireless sensor networks(WSNs).Adversaries may use RF(radio frequency) localization techniques to perform hop-by-hop trace back to the source sensor's location.A multiple k-hop clusters based routing strategy(MHCR) is proposed to preserve source-location privacy as well as enhance energy efficiency for WSNs.Owing to the inherent characteristics of intra-cluster data aggregation,each sensor of the interference clusters is able to act as a fake source to confuse the adversary.Moreover,dummy traffic could be filtered efficiently by the cluster heads during the data aggregation,ensuring no energy consumption be burdened in the hotspot of the network.Through careful analysis and calculation on the distribution and the number of interference clusters,energy efficiency is significantly enhanced without reducing the network lifetime.Finally,the security and delay performance of MHCR scheme are theoretically analyzed.Extensive analysis and simulation results demonstrate that MHCR scheme can improve both the location privacy security and energy efficiency markedly,especially in large-scale WSNs.

TDOA Localization Algorithm with Compensation of Clock Offset for Wireless Sensor Networks

This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.

Research of variable speed directly driven SRG wind power system position sensorless based on DFNN by FEA

A new method of switched reluctance wind power generation position sensorless based on DFNN by FEA was proposed, Through current and magnetic linkage to get the angle of SRG rotor position, the nonlinear mapping of cur- rent-magnetic linkage-angle was built, By training these sample data from FEA, the angle of SRG rotor position was replaced by the output of DFNN to achieve SRG position sensorless. Simulation results show that the error between actual rotor position and estimate rotor position is small; SRG can commutate with great accuracy; and the output voltage of SRG wind power system under variable wind speed is essentially constant.

A Precise RFID Indoor Localization System with Sensor Network Assistance

Indoor localization is very critical for medical care applications, e.g., the patient localization or tracking inside the building of the hospital. Traditional Radio Frequency Identification(RFID) technologies are very popular in this area since their cost is very low. In such technologies, each tag acts as the transmitter and the Radio Signal Strength Indicator(RSSI) information is measured from the readers. However, RSSI information suffers severely from the multi- path phenomenon. As a result, if in a very large area, the localization accuracy will be affected seriously. In order to solve this problem, we introduce Wireless Sensor Networks(WSNs) with only a few nodes, each of which acts as both transmitter and receiver. In such networks, the change of signal strength(referred as dynamic of RSSI) is leveraged to select a cluster of reference tags as candidates. Then the fi nal target location is estimated by using the RSSI relationships between the target tag and candidate reference tags. Thus, the localization accuracy and scalability are able to be improved. We proposed two algorithms, SA-LANDMARC, and COCKTAIL. Experiments show that the localization accuracy of the two algorithms can reach 0.7m and 0.45 m, respectively. Compared to most traditional Radio Frequency(RF)-based approaches, the localization accuracy is improved at least 50%.

Free Search Algorithm Based Estimation in WSN Location

This paper proposes a novel intelligent estimation algorithm in Wireless Sensor Network nodes location based on Free Search,which converts parameter estimation to on-line optimization of nonlinear function and estimates the coordinates of senor nodes using the Free Search optimization.Compared to the least-squares estimation algorithms,the localization accuracy has been increased significantly,which has been verified by the simulation results.

A New Localization Scheme with Statistical Estimation against Wormhole Attack in Wireless Sensor Networks

Wormhole attack is one of the most devastating threats for range-free localization in wireless sensor networks. In this paper, we evaluate three statistical estimation methods with the same network model and geographic information obtailaed by the DV-Hop algorithm. We analyze the limits of Minimum Mean Square Estimate （MMSE）, Least Median of Squares （LMS） and Enhanced greedy At- tack-Resistant MMSE （EARMMSE） and propose an improved EARMMSE with the hop-distance relationship, named EARMMSE＋. Simulation results illustrate the performance of MMSE, LMS and EARMMSE＋ with different anchor fraction, the length of wormhole link and the average local neighborhood and show that EARMMSE＋ outperforms MMSE and LMS.

An Iterative Clustering-Based Localization Algorithm for Wireless Sensor Networks

In wireless sensor networks,node localization is a fundamental middleware service.In this paper,a robust and accurate localization algorithm is proposed,which uses a novel iterative clustering model to obtain the most representative intersection points between every two circles and use them to estimate the position of unknown nodes.Simulation results demonstrate that the proposed algorithm outperforms other localization schemes (such as Min-Max,etc.) in accuracy,scalability and gross error tolerance.

LOCALIZATION ALGORITHM BASED ON MINIMUM CONDITION NUMBER FOR WIRELESS SENSOR NETWORKS

During range-based self-localization of Wireless Sensor Network (WSN) nodes, the number and placement methods of beacon nodes have a great influence on the accuracy of localization. This paper proves a theorem which describes the relationship between the placement of beacon nodes and whether the node can be located in 3D indoor environment. In fact, as the highest locating accuracy can be acquired when the beacon nodes form one or more equilateral triangles in 2D plane, we generalizes this conclusion to 3D space, and proposes a beacon nodes selection algorithm based on the minimum condition number to get the higher locating accuracy, which can minimize the influence of distance measurement error. Simulation results show that the algorithm is effective and feasible.

Wireless location technology and its application

Wireless location technology is used to locate,track and monitor the location of given target using devices such as the radio frequency identification(RFID) based on WiFi technology and the sensors. And such applications as long term evolution(LTE) ,wireless local area networks(WLAN) ,RFID and location based service(LBS) are essential in today's wireless communications industry. In this paper,both wireless location technology and its application are proposed,where our experimental research results and theoretical innovation are included.

Position Sensorless Torque Estimation of Synchronous Reluctance Motors Based on Extended-Flux Model without Core-Loss Measurement

This paper proposes an extended-flux model with core-loss resistance of SynRMs （synchronous reluctance motors） and precise torque estimation without core-loss measurement and position encoder. The proposed torque estimation is useful for precise MTPA （maximum torque per ampere） control of position sensorless controlled SynRMs, which is achieved with the assistance of active and reactive powers.

Robot Positioning and Navigation Based on Hybrid Wireless Sensor Network

Traditional sensor network and robot navigation are based on the map of detecting the fields available in advance. The optimal algorithms are developed to solve the energy saving, the shortest path problems, etc. However, in the practical enviroranent, there are many fields, whose map is difficult to get, and needs to be detected. In this paper a kind of ad-hoc navigation algorithm is explored, which is based on the hybrid sensor network without the prior map in advance. The navigation system is composed of static nodes and dynamic trades. The static nodes monitor the occurrances of the events and broadcast them. In the syston, a kind of algorithm is to locate the rdbot, which is based on duster broadcasting. The dynamic nodes detect the adversary or dangerous fields and broadcast warning messages. The robot gets the message and follows ad-hoc routine to arrive where the events occur. In the whole process, energy saving has been taken into account. The algorithms, which are based on the hybrid sensor network, are given in this paper. The simulation and practical results are also available.

An efficient range-free localization algorithm for wireless sensor networks

Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm.

An area-based position and attitude estimation for unmanned aerial vehicle navigation

The paper aims to challenge non-GPS navigation problems by using visual sensors and geo-referenced images. An area-based method is proposed to estimate full navigation parameters(FNPs), including attitude, altitude and horizontal position, for unmanned aerial vehicle(UAV) navigation. Our method is composed of three main modules: geometric transfer function, local normalized sobel energy image(LNSEI) based objective function and simplex-simulated annealing(SSA) based optimization algorithm. The adoption of relatively rich scene information and LNSEI, makes it possible to yield a solution robustly even in the presence of very noisy cases, such as multi-modal and/or multi-temporal images that differ in the type of visual sensor, season, illumination, weather, and so on, and also to handle the sparsely textured regions where features are barely detected or matched. Simulation experiments using many synthetic images clearly support noise resistance and estimation accuracy, and experimental results using 2367 real images show the maximum estimation error of 5.16(meter) for horizontal position, 9.72(meter) for altitude and 0.82(degree) for attitude.

Improved Algorithm for Distributed Localization in Wireless Sensor Networks

Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.