An online optimum voltage estimation and real‐time MPP tracking for a PV system

In this paper, a photovoltaic system topology incorporating a new maximum power point tracking (MPPT) controller method is presented. This method uses an autotuning estimator and a PI controller to make the system work in the maximum power point. The controller is formulated based on the bijectivity in the photovoltaic generator characteristic; therefore, if the optimal voltage is reached, this means that the maximum of power is obtained. The proposed MPPT algorithm is implemented on a dSpace DS1104 controller board. In order to demonstrate the efficiency of the proposed algorithm in real time, an experimental setup using a boost converter connected to a resistive load is successfully implemented and studied. The obtained experimental results prove the validity of the proposed MPPT algorithm.     

Single Beacon Cruise Positioning Algorithm in Wireless Sensor Networks

Node localization is important in WSNs （Wireless sensor networks） applications. We present a new cruise positioning algorithm, where a single beacon node cruises an entire network, broadcasting its position periodically with fixed signal strength. Meawhile, an unknown node obtains the location and the corresponding distance of the beacon node. Two possible position coordinate sets for the unknown node can then be calculated, and the coordinate mean of the point set with a small variance is an unbiased estimator of the unknown node＇s coordinate. The positioning algorithm＇s computation is simple, positioning accuracy is not limited by a physical distance measuring tool, and there are no restrictions on the path of motion, which makes it more realistic. An algorithm simulation is presented to compare the original and cruise location algorithm. Numerical results show that the cruise localization algorithm can achieve good positioning accuracy.     

Limit behaviors of extended Kalman filter as a parameter estimator for a sinusoidal signal

In this note, the basic limit behaviors of the solution to Riccati equation in the extended Kalman filter as a parameter estimator for a sinusoidal signal are analytically investigated by using lim sup and lim inf in advanced calculus. We show that if the covariance matrix has a limit, then it must be a zero matrix.     

Adaptive force–environment estimator for manipulators based on adaptive wavelet neural network

This study focuses on the accurate tracking control and sensorless estimation of external force disturbances on robot manipulators. The proposed approach is based on an adaptive Wavelet Neural Network (WNN), named Adaptive Force-Environment Estimator (WNN-AFEE). Unlike disturbance observers, WNN_AFEE does not require the inverse of the Jacobian transpose for computing the force, thus, it has no computational problem near singular points. In this scheme, WNN estimates the external force disturbance to attenuate its effects on the control system performance by estimating the environment model. A Lyapunov based design is presented to determine adaptive laws for tuning WNN parameters. Another advantage of the proposed approach is that it can estimate the force even when there are some parametric uncertainties in the robot model, because an additional adaptive law is designed to estimate the robot parameters. In a theorem, the stability of the closed loop system is proved and a general condition is presented for identifying the force and robot parameters. Some suggestions are provided for improving the estimation and control performance. Then, a WNN-AFEE is designed for a planar manipulator as an example, and some simulations are performed for different conditions. WNN_AFEE results are compared attentively with the results of an adaptive force estimator and a disturbance estimator. These comparisons show the efficiency of the proposed controller in dealing with different conditions.     

ASYMPTOTIC INFERENCES FOR AN AR(1) MODEL WITH A CHANGE POINT: STATIONARY AND NEARLY NON‐STATIONARY CASES

This article examines the asymptotic inference for AR(1) models with a possible structural break in the AR parameter β near the unity at an unknown time k₀. Consider the model y_t = β₁y_{t − 1}I{t ≤ k₀} + β₂y_{t − 1}I{t > k₀} + ϵ_t, t = 1,2, … ,T, where I{ ⋅ } denotes the indicator function. We examine two cases: case I | β₁ | < 1,β₂ = β_2T = 1 − c ∕ T; and case II β₁ = β_1T = 1 − c ∕ T, | β₂ | < 1, where c is a fixed constant, and {ϵ_t,t ≥ 1} is a sequence of i.i.d. random variables, which are in the domain of attraction of the normal law with zero means and possibly infinite variances. We derive the limiting distributions of the least squares estimators of β₁ and β₂ and that of the break‐point estimator for shrinking break for the aforementioned cases. Monte Carlo simulations are conducted to demonstrate the finite‐sample properties of the estimators. Our theoretical results are supported by Monte Carlo simulations.     

Safe mobility for elderly drivers—Considerations based on expert and self-assessment

To further understand the needs of the growing population of elderly drivers and create solutions for safe mobility it is important to understand the driving scenarios and aspects in day to day traffic that may be of challenge for this group. More so, individual differences in how drivers perceive their own driving ability may have an effect on how individuals limit their mobility and/or increase their exposure to risk situations, with a potential negative effect on safety.     

An Improved Maximum Exponentially Weighted Moving Average Control Chart for Monitoring Process Mean and Variability

Maximum exponentially weighted moving average (MaxEWMA) control charts have gained considerable attention for detecting changes in both process mean and process variability. In this paper, we propose an improved MaxEWMA control charts based on ordered ranked set sampling (ORSS) and ordered imperfect ranked set sampling (OIRSS) schemes for simultaneous detection of both increases and decreases in the process mean and/or variability, named MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts. These MaxEWMA control charts are based on the best linear unbiased estimators of location and scale parameters obtained under ORSS and OIRSS methods. Extensive Monte Carlo simulations have been used to estimate the average run length and standard deviation of run length of the proposed MaxEWMA control charts. These control charts are compared with their counterparts based on simple random sampling (SRS), that is, MaxEWMA‐SRS and MaxGWMA‐SRS control charts. The proposed MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts are able to perform better than the MaxEWMA‐SRS and MaxGWMA‐SRS control charts for detecting shifts in the process mean and dispersion. An application to real data is provided to illustrate the implementation of the proposed MaxEWMA control charts. Copyright © 2013 John Wiley & Sons, Ltd.     

基于无源性的并联型有源电力滤波器控制策略

非线性负载的变化是影响有源电力滤波器(APF)稳定控制的主要因素之一,基于无源性的控制(PBC)方法为此提供了有效的解决方案.利用本质上是非线性反馈的PBC策略,从能量角度分析并联型APF控制系统,确定不必抵消的"无功力",设计全局定义的控制律,实现APF系统的全局稳定和电流跟踪控制.首先建立了三相APF的Euler-Lagrange模型;在此基础上利用PBC方法构建电流动态跟踪控制器,在非线性负载时变未知情形下,实现了直流侧电容电压的补偿控制和谐波电流的期望轨迹渐近跟踪;最后,针对实际运行时APF系统参数具有不确定性的问题,将PBC方法与非线性观测算法相结合,实现电阻参数的自调整,有效抑制负载变化时产生的电流畸变.该方法具有形式简单、无奇异点、鲁棒性好的特点.基于dSPACE的实验结果证明了该控制策略的有效性.     

异步电机速度控制系统中控制器的研究

由于在直接转矩控制系统中异步电机的转矩并非恒定;且源于控制系统的速度环输出没有对电机转矩进行解耦,并不能明确地知道给定转矩和实际转矩的关系。为获得优良的控制品质,在直接转矩控制的基础上,使用模糊逻辑控制器,把速度调节与直接转矩控制中的施密特触发器阈值相联系,减少开关元件的动作次数;采用具有自学习功能的控制器作为控制系统的速度调节器,借助其自学习功能,控制器不断地修改隶属函数参数以适应实际工况,实现非线性P ID控制器参数的实时优化调整,直到系统性能达到预期要求为止。与传统的控制器相比,它可以在一定程度上提高系统的动态控制性能。