Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

Roll-pitch-yaw autopilot design for nonlinear time-varying missile using partial state observer based global fast terminal sliding mode control

The acceleration autopilot design for skid-to-turn （STT） missile faces a great challenge owing to coupling effect among planes, variation of missile velocity and its parameters, inexistence of a complete state vector, and nonlinear aerodynamics. Moreover, the autopilot should be designed for the entire flight envelope where fast variations exist. In this paper, a design of integrated roll-pitch-yaw autopilot based on global fast terminal sliding mode control （GFTSMC） with a partial state nonlinear observer （PSNLO） for STT nonlinear time-varying missile model, is employed to address these issues. GFTSMC with a novel sliding surface is proposed to nullify the integral error and the singularity problem without application of the sign function. The proposed autopilot consisting of two-loop structure, controls STT maneuver and stabilizes the rolling with a PSNLO in order to estimate the immeasurable states as an output while its inputs are missile measurable states and control signals. The missile model considers the velocity variation, gravity effect and parameters＇ variation. Furthermore, the environmental conditions＇ dynamics are mod- eled. PSNLO stability and the closed loop system stability are studied. Finally, numerical simulation is established to evaluate the proposed autopilot performance and to compare it with existing approaches in the literature.

Global fast and slow solutions of a localized problem with free boundary

In this paper,we consider a localized problem with free boundary for the heat equation in higher space dimensions and heterogeneous environment.For simplicity,we assume that the environment and solution are radially symmetric.First,by using the contraction mapping theorem,we prove that the local solution exists and is unique.Then,some sufficient conditions are given under which the solution will blow up in finite time.Our results indicate that the blowup occurs if the initial data are sufficiently large.Finally,the long time behavior of the global solution is discussed.It is shown that the global fast solution does exist if the initial data are sufficiently small,while the global slow solution is possible if the initial data are suitably large.

Blowup, Global Fast and Slow Solutions for a Semilinear Combustible System

In this paper, we investigate a semilinear combustible system ut-duxx = vP, vt-dvxx = uq with double fronts free boundary, where p ≥1,q ≥ 1. For such a prob- lem, we use the contraction mapping theorem to prove the local existence and uniqueness of the solution. Also we study the blowup and global existence property of the solution. Our results show that when pq 〉 1 blowup occurs if the initial datum is large enough and the solution is global and slow, whose decay rate is at most polynomial if the initial value is suitably large, while when p 〉 1, q 〉 1 there is a global and fast solution, which decays uniformly at an exponential rate if the initial datum is small.

Application of global variance reduction method to calculate a high-resolution fast neutron flux distribution for TMSR-SF1

The solid fuel thorium molten salt reactor(TMSR-SF1) is a 10-MWth fluoride-cooled pebble bed reactor. As a new reactor concept, one of the major limiting factors to reactor lifetime is radiation-induced material damage. The fast neutron flux(E > 0.1 MeV) can be used to assess possible radiation damage. Hence, a method for calculating high-resolution fast neutron flux distribution of the full-scale TMSR-SF1 reactor is required. In this study,a two-step subsection approach based on MCNP5 involving a global variance reduction method, referred to as forward-weighted consistent adjoint-driven importance sampling, was implemented to provide fast neutron flux distribution throughout the TMSR-SF1 facility. In addition,instead of using the general source specification cards, the user-provided SOURCE subroutine in MCNP5 source code was employed to implement a source biasing technique specialized for TMSR-SF1. In contrast to the one-step analog approach, the two-step subsection approach eliminates zero-scored mesh tally cells and obtains tally results with extremely uniform and low relative uncertainties.Furthermore, the maximum fast neutron fluxes of the main components in TMSR-SF1 are provided, which can be used for radiation damage assessment of the structural materials.

An adaptive finite-difference method for seismic traveltime modeling based on 3D eikonal equation

3D eikonal equation is a partial differential equation for the calculation of first-arrival traveltimes and has been widely applied in many scopes such as ray tracing,source localization,reflection migration,seismic monitoring and tomographic imaging.In recent years,many advanced methods have been developed to solve the 3D eikonal equation in heterogeneous media.However,there are still challenges for the stable and accurate calculation of first-arrival traveltimes in 3D strongly inhomogeneous media.In this paper,we propose an adaptive finite-difference(AFD)method to numerically solve the 3D eikonal equation.The novel method makes full use of the advantages of different local operators characterizing different seismic wave types to calculate factors and traveltimes,and then the most accurate factor and traveltime are adaptively selected for the convergent updating based on the Fermat principle.Combined with global fast sweeping describing seismic waves propagating along eight directions in 3D media,our novel method can achieve the robust calculation of first-arrival traveltimes with high precision at grid points either near source point or far away from source point even in a velocity model with large and sharp contrasts.Several numerical examples show the good performance of the AFD method,which will be beneficial to many scientific applications.

基于干扰观测器与终端滑模的车辆纵向控制

为了消除未知干扰和不确定性对车辆纵向控制的影响,设计了基于干扰观测器和终端滑模控制的分层式车辆纵向控制系统.利用干扰观测器对系统干扰进行实时观测,实现对系统的反馈补偿,降低滑模控制的切换增益,从而抑制滑模控制的抖振.利用Lyapunov函数证明了控制系统的稳定性,并通过Carsim/Simulink进行了联合仿真试验.结果表明:在两种仿真工况条件下,控制器对参考速度跟踪效果良好,速度误差最大仅为0.22 m/s,干扰观测器对系统干扰能够准确快速估计,估计误差仅为0.003 14,切换逻辑执行器发挥良好;与传统滑模控制相比,所设计的控制器稳定性更好,抑制了滑模控制的抖振,实现了对车辆纵向速度的稳定跟踪.

基于改进模糊滑模控制的列车速度跟踪研究

列车运行过程具有强耦合、非线性等特征,且往往存在较大且不可观测的外界干扰,这些特性加大了列车运行控制的难度,针对列车运行速度跟踪控制问题,提出一种新的模糊滑模控制器设计方法。首先基于模糊滑模控制,引入全局快速终端滑模控制,使系统在有限时间内达到稳态;然后构造以李亚普洛夫函数导数的绝对值为补偿的自适应干扰估计项,对外界干扰进行准确估计,进而提出一种双层递阶指数趋近全局快速终端模糊滑模控制器,并且引入指数趋近率来调节滑模面的动态品质,该控制器能快速收敛到稳定状态,且有效地消除了控制器的抖振情况;最后通过仿真算例验证了所提方法的有效性,且提高了列车运行控制系统性能。

基于全局快速终端滑模的6-PSS并联运动模拟器轨迹跟踪控制研究

针对6-PSS并联运动模拟器动力学模型中的不确定性和时变扰动,提出了一种基于全局快速终端滑模的鲁棒控制策略。首先,运用虚功原理建立了该机构的动力学模型(该动力学模型表明6-PSS并联机构是一个具有非线性和强耦合特性的多变量系统),对动力学模型进行了离线处理,使其反映出机构真实动力学特性,并满足设备实时计算能力的要求;然后,基于简化后的动力学模型设计了一种全局快速终端滑模控制器(GFTSMC),设计李雅普诺夫(Lyapunov)函数对控制律进行了分析,证明了控制器的稳定性;最后,将控制策略应用于6-PSS并联运动模拟器轨迹跟踪控制,并将其与PD前馈控制及传统滑模控制(SMC)进行了对比实验。研究结果表明:GFTSMC相对于PD和SMC的平均误差分别下降了82.92%和18.88%,标准差分别下降了80.03%和41.73%,且能够起到抑制抖振的效果,是6-PSS并联运动模拟器的一种有效且实用的鲁棒控制方案。该研究结果可为6-PSS并联运动模拟器控制及工程应用提供理论依据。

基于Extend FAST方法的新安江模型参数全局敏感性分析

模型参数敏感性分析可以诊断模型结构、识别模型关键参数,是模型建立和应用的关键步骤。该文应用高效、稳健的Extend FAST方法,以流溪河水库入库洪水模拟为例分析新安江模型参数的全局敏感性。结果表明,对Nash-Sutcliffe效率系数、总水量平衡误差系数、低水流量误差系数、高水流量误差系数四个目标函数,模型参数敏感性表现不同。Extend FAST方法的部分结果与GLUE方法的结果进行对比,两者对敏感性评价的结果基本一致,Extend FAST给出的主要敏感度和参数组合作用的敏感度也可以作为模型不确定性分析的依据。

Trajectory tracking and obstacle avoidance method for robots based on fast terminal sliding mode

For accurate trajectory tracking and obstacle avoidance in finite time of a nonholonomic mobile robot,a trajectory tracking controller based on global fast terminal sliding mode method is proposed,which has the advantages of chattering-free and adjustable convergence time.First of all,the kinematics model of the robot is established in mobile carrier coordinates.Secondly,the global structure including terminal attractor and exponential convergence of the fast terminal sliding mode trajectory tracking controller is proved by Lyapunov stability theory,ensuring that the trajectory and heading angle tracking error converges to a smaller zero range in finite time.Finally,the artificial potential field obstacle avoidance method is introduced to make the robot not only track the reference trajectory strictly,but also avoid the obstacles.The simulation results show that the proposed method can achieve a stable tracking control in finite time for a given reference trajectory.

基于改进FAST特征匹配的电子稳像算法

针对机载摄像机视频抖动问题,提出了基于改进FAST的特征匹配方法,去除视频序列的帧间抖动,实现视频序列的电子稳像。提出了尺度空间的FAST特征提取方法,结合了优化的SURF描述算子,利用相邻帧的特征点进行匹配,消除视频的帧间旋转量,得到帧间的局部运动矢量,然后通过RANSAC算法求解出全局运动矢量,最后利用二次线性插值算法逐帧补偿。实验结果表明,稳像后的视频帧间PSNR提高5dB,提出的稳像算法去除了视频帧间复杂抖动,且快速准确并具有一定的鲁棒性。

A Bio-Inspired Global Finite Time Tracking Control of Four-Rotor Test Bench System

A bio-inspired global finite time control using global fast-terminal sliding mode controller and radial basis function network is presented in this article,to address the attitude tracking control problem of the three degree-of-freedom four-rotor hover system.The proposed controller provides convergence of system states in a predetermined finite time and estimates the unmodeled dynamics of the four-rotor system.Dynamic model of the four-rotor system is derived with Newton’s force equations.The unknown dynamics of four-rotor systems are estimated using Radial basis function.The bio-inspired global fast terminal sliding mode controller is proposed to provide chattering free finite time error convergence and to provide optimal tracking of the attitude angles while being subjected to unknown dynamics.The global stability proof of the designed controller is provided on the basis of Lyapunov stability theorem.The proposed controller is validated by(i)conducting an experiment through implementing it on the laboratory-based hover system,and(ii)through simulations.Performance of the proposed control scheme is also compared with classical and intelligent controllers.The performance comparison exhibits that the designed controller has quick transient response and improved chattering free steady state performance.The proposed bioinspired global fast terminal sliding mode controller offers improved estimation and better tracking performance than the traditional controllers.In addition,the proposed controller is computationally cost effective and can be implanted on multirotor unmanned air vehicles with limited computational processing capabilities.

线控制动系统主缸液压力滑模控制鲁棒性分析

针对一种全解耦式线控液压制动系统制动主缸液压力控制过程中,易受系统参数不确定性和外界摄动量等因素的干扰,从而造成制动主缸液压力控制过程中出现振荡、爬行等问题,提出了一种综合考虑系统不利因素影响的主缸液压力全局快速滑模鲁棒控制算法。通过对制动主缸动力学模型的简化,建立了含有干扰项的主缸液压力控制参考模型,并在此基础上设计了鲁棒控制律和主缸液压力滑模控制器;此外,定义了Lyapunov函数对制动压力控制系统滑模到达时间、稳定性和收敛性进行分析。通过MATLAB/Simulink、AMESim联合仿真,对该线控制动主缸液压力控制策略进行验证和评价,结果表明所提出的液压力控制策略具有很好的鲁棒性和稳定性,并能精确跟踪期望压力,且响应迅速。

基于FAST方法的核动力装置非能动系统全局参数敏感性分析

为提高核动力装置非能动系统参数敏感性分析的精度和效率,实现更加精确的非能动系统热工水力行为分析、识别对系统运行有重要影响的因素,因此采用FAST方法以某型非能动余热排出试验系统的热工水力模型作为算例进行了全局参数敏感性分析研究。分析结果表明:电加热功率、冷凝器换热管污垢因子、热阱温度、热阱压力这4个参数对系统行为的影响较为显著,需在系统优化设计、运行管理过程中进行适当改进、监测。

一种二级分段PMF-FFT卫星信号捕获算法

针对在小点数快速傅里叶变换(Fast Fourier Transform,FFT)中,经典分段匹配滤波(Partial Matched Filtering,PMF)与FFT相结合的PMF-FFT卫星信号捕获算法存在增益损失,导致捕获灵敏度低、频率覆盖范围小和搜索速度慢的问题,提出了一种改进的二级分段PMF-FFT卫星信号捕获算法。截取部分FFT频率分量,缩短算法有效频率覆盖范围,以改善分段求和带来的包络增益衰减;采用在FFT频率分量中间位置追加搜索的方法,以改善FFT带来的扇贝损失;使用从粗略搜索到高精度搜索的策略,以减少搜索次数,提高搜索速度。仿真结果表明,相比经典PMF-FFT算法,在FFT点数不大于64点的情况下,改进算法能有效提高搜索增益和搜索速度,在8点FFT、125 Hz频率精度条件下,平均增益提升了22.19%,搜索次数减少了7.69%。

Critical Exponents for Fast Diffusion Equations with Nonlinear Boundary Sources

In this paper,we study the large time behavior of solutions to a class of fast diffusion equations with nonlinear boundary sources on the exterior domain of the unit ball.We are interested in the critical global exponent q_o and the critical Fujita exponent q_c for the problem considered,and show that q_o=q_c for the multidimensional Non-Newtonian polytropic filtration equation with nonlinear boundary sources,which is quite different from the known results that q_o〈q_c for the onedimensional case;moreover,the value is different from the slow case.

基于改进型双幂次趋近律与全局快速终端滑模观测器的IPMSM调速系统滑模控制

针对内置式永磁同步电机(IPMSM)速度环中存在的内部参数摄动与外部负载扰动等问题,为了提高速度控制系统的动态性和鲁棒性,该文提出一种基于改进型双幂次趋近律(IDPRL)与全局快速终端滑模观测器(GFTSMO)的滑模控制方法。所提趋近律在幂次项中引入系统状态变量,减少了稳态误差,解决了快速趋近滑模面和抖振抑制之间的矛盾。设计一种基于IDPRL的IPMSM滑模速度控制器。为了进一步减少系统状态的稳态误差,设计了一种GFTSMO,该观测器不仅能够减少趋近律的开关增益,还能实现系统扰动的准确补偿。仿真和实验结果验证了所提的滑模控制方法的可行性和有效性。

基于全局和局部特征的图像快速拼接算法

为了提升图像快速拼接效果,提出了基于全局和局部特征的图像快速拼接算法,利用改进形状上下文算法,提取图像全局形状特征,按照轮廓点序列间最小欧式距离完成图像粗匹配。通过关键点提取算法提取原始图像与粗匹配图像的局部特征,利用应用随机抽样一致性方法根据局部特征进行图像精匹配,通过渐入渐出融合算法融合精匹配图像拼接时重叠区域的边缘,完成图像快速无缝拼接。实验证明:该算法在图像模糊与视角变换时,均可有效快速拼接图像,拼接后的图像清晰度佳、细节信息含量多,获得理想的图像拼接效果。

微纳卫星动量轮神经网络全局快速终端滑模控制

针对存在参数不确定性和外界未知干扰的微纳卫星动量轮转速跟踪控制问题,建立了包含模型不确定性和外部干扰的动量轮系统动力学模型,并提出了一种自适应神经网络全局快速终端滑模控制方法。首先,在无外部干扰情况下,设计了全局快速终端滑模控制策略以加快系统响应速度,实现系统有限时间稳定。其次,利用径向基函数神经网络对系统参数不确定性和外部干扰进行估计并补偿,并利用李雅普诺夫方法推导出神经网络自适应律,通过自适应调节网络权值确保系统在存在干扰的情况下实现系统稳定。最后通过仿真对比验证,本文设计的控制器不仅响应速度快,而且具有更好的抗干扰能力和鲁棒性。