波浪能液压转换装置的非线性状态空间模型的建立

海洋波浪能被认为是全球很有潜力的可再生能源。提出使用漂浮式浮子吸收波浪能,再利用液压功率输出机械将吸收来的能量转换为电能。对于波浪能发电,关键在于效率的提高以及发电质量的稳定。设计的液压功率输出装置可以双向输出高压油,从而大大提高了波浪能转换效率,而且装置中的高压蓄能器对发电质量的稳定起关键作用。基于线性水动力学理论,推导出振荡浮子式波浪能转换装置的数值模型。该模型考虑了液压系统内部件的滑动摩擦力和高压油流经阀门时节流孔的压降。由于该液压功率输出机械是非线性系统,推导出整个波浪能转换装置系统的非线性状态空间模型。

基于非线性混合效应状态空间模型的粒子滤波

粒子滤波算法是一种用于解决非线性系统问题的新型算法。通常粒子滤波利用重要性重抽样算法,选用先验分布,但是其易受外部观测值影响,从而导致权重变化较大。为此,文中引入辅助粒子滤波算法进行改进,该算法优势在于前一时刻的样本在抽取时以当前的观测数据为条件,这样得到的样本更加接近真实状态。最后,通过仿真实例,进一步分析验证了辅助粒子滤波算法比采样重要性重抽样更为有效。

基于支持向量机N4SID辨识模型的非线性预测控制

针对工业控制领域中非线性系统的模型辨识与预测控制问题,采用最小二乘支持向量机回归方法构造非线性函数,运用状态子空间(N4SID)模型辨识方法辨识非线性状态空间模型.在此基础上建立非线性预测控制器,利用拟牛顿算法进行非线性预测控制律的求解,从而实现了一种新的基于支持向量机N4SID辨识模型的非线性预测控制算法.仿真实验验证了该算法的有效性和可行性.

数字液压缸非线性动态特性分析及试验

综合考虑阀芯螺旋运动和反馈机构动态,修正阀口流量方程,并基于Lu Gre摩擦模型推导得到了完整的数字液压缸非线性状态空间模型。对三种不同模型进行仿真并以试验为参考,验证了非线性模型的准确性,并利用所建模型重点分析了系统换向时的动态特性。结果表明:非线性模型能更真实地反映系统的响应特性;不平衡冲击与摩擦Stribeck效应耦合导致换向速度抖动,同时受工作压力、死区、阀芯径向泄漏、Stribeck速度和反馈机构刚度等非线性因素的共同影响,速度抖动状况呈现出多变性。

非线性模型空间非线性平差模型的处理方法

讨论了参数效应非线性贡献因子的处理方法.基于真误差的定义,给出了GMSE的定义,以此为基础,提出了以新的平差准则—GSMSE为基础的非线性平差模型的综合处理方法.作为实例,在非线性模型空间,借助迭代技术,研究了非线性回归模型的解,并对线性模型空间与非线性模型空间的解进行比较.表4,参8.

旅游产业发展的减贫效应与空间政策选择

通过考察旅游产业发展与贫困减缓影响关系,利用空间非线性效应因素,采用非线性Granger因果模型就旅游产业与城镇贫困和农村贫困进行了实证检验。同时运用时空地理加权模型(GTWR)检验我国旅游产业与城镇贫困和农村贫困的空间异质性特征,以2000—2017年中国31个省区为研究对象,通过空间半参数非线性Durbin模型构建和估计,就我国旅游减贫的空间外溢效应进行分析。实证结果表明:我国旅游产业发展、旅游产业集聚、经济发展和经济集聚对城镇贫困和农村贫困都具有正向的空间溢出效应。因此,建议加大旅游扶贫政策支持力度,完善旅游设施建设,创新旅游业态产品,构建旅游产业人才引进与培训体系,加强旅游减贫的区域合作,不断提升旅游产业发展的减贫效应。

财政偏向、农村劳动力转移与城乡收入差距

基于2002—2020年中国30个省份面板数据,运用非线性空间杜宾模型分析财政偏向对城乡收入差距的影响效应,并进一步考察农村劳动力转移的调节作用。结果表明:财政偏向对城乡收入差距的直接影响效应和空间溢出效应均呈倒“U”型特征,即达到一定阈值后,财政偏向会缩小本地和周边地区的城乡收入差距;财政偏向对城乡收入差距的作用效果存在基于经济发展水平差异的区域异质性;农村劳动力转移在财政偏向与城乡收入差距之间发挥调节作用,且该作用效果存在区域异质性,即随着农村劳动力转移程度的提高,财政偏向与城乡收入差距之间的关系曲线趋向陡峭,同时曲线拐点向左移动。据此,建议因地制宜确定财政支农规模,重视加强区域间协同发展机制,促进农村劳动力自由转移,进而推动城乡一体化发展。

基于观测数据的时间序列因果推断综述

数据存储量的扩大和计算能力的提升为基于观测数据推断时间序列的因果关系开辟了新途径。在时间序列因果推断的基本性质和研究现状的基础上,系统梳理了5种基于观测数据的时间序列因果推断方法,即Granger因果分析方法、基于信息论的方法、因果网络结构学习算法、基于结构因果模型的方法和基于非线性状态空间模型的方法。然后,根据不同应用场景的数据特点,结合方法的功能和适配性,对基于观测数据的时间序列因果推断方法在经济金融、医疗和生物学、地球系统科学和其他工程领域的典型应用进行了简要介绍。最后,结合时间序列因果推断的重难点问题,比较5种方法的优缺点,分析下一步研究重点,展望未来的研究方向。

基于无迹Kalman滤波的基波分量提取

针对全波Fourier和Kalman滤波算法在提取基波分量时对频率偏移敏感和直流偏移量抑制能力差的缺点,提出了一种新的基波分量提取算法。首先以故障信号的直流偏移量、基波角频率和基波分量作为状态变量,建立信号的非线性状态空间模型。然后采用无迹Kalman滤波(Unscented Kalman Filter,UKF)在信号的非线性模型基础上估计出基波分量。此外,滤波算法还能够实时估计出信号的直流偏移量和基波频率。通过多个算例仿真对算法进行验证与测试,仿真结果证实了算法的可行性和有效性。仿真结果表明,算法对频率突变和直流偏移量突变具有良好的适应性,能快速准确地提取出基波分量。

环境规制与产业结构调整:“本地-邻地”效应与传导机制

现有研究大多关注环境规制政策对产业结构调整升级的作用,却普遍忽视环境规制可能对“本地—邻地”产业结构调整的影响与传导机制。论文基于2008—2017年长三角区域“三省一市”41个地级市的数据,采用非线性空间杜宾面板模型进行实证研究,结果发现:环境规制对“本地”产业结构调整有显著的促进作用,且峰值出现在400~500千米范围内;对“邻地”产业结构调整短期起抑制作用,在长期转为促进作用。进一步的传导机制检验表明,不同程度的环境规制对产业结构调整的异质性可能由于环境规制引发工业跨区域转移、长期邻地的收入效应使得产业结构调整呈现为“U”型。论文深化了环境规制与产业结构调整研究,为促进城市高质量发展提供了不同的思路和政策建议。

Processing Approach of Non-linear Adjustment Models in the Space of Non-linear Models

This paper investigates the mathematic features of non-linear models and discusses the processing way of non-linear factors which contributes to the non-linearity of a non-linear model. On the basis of the error definition,this paper puts forward a new adjustment criterion, SGPE.Last,this paper investigates the solution of a non-linear regression model in the non-linear model space and makes the comparison between the estimated values in non-linear model space and those in linear model space.

聚丙烯装置气相聚合生产过程预测控制系统的研究与实现

本文针对聚丙烯装置气相聚合生产过程存在的常规控制问题,提出了基于机理模型和非线性状态空间多变量预测控制系统的解决方案。依据乙烯与丙烯多元共聚反应机理和反应动力学方程,建立熔融指数、乙烯质量分率等气相聚合单元质量指标软测量机理模型。采用非线性状态空间多变量预测控制算法,结合单值预测控制、多控制周期、多预测时域的控制思想,深入研究气相聚合预测控制系统的控制策略。

Dynamic analysis and nonlinear identification of space deployable structure

The dynamic equivalent continuum modeling method of the mast which is based on energy equivalency principle was investigated. And three kinds of mast dynamic model were established, which were equivalent continuum model, finite element model and simulation model, respectively. The mast frequencies and mode shapes were calculated by these models and compared with each other. The error between the equivalent continuum model and the finite element model is less than 5% when the mast length is longer. Dynamic responses of the mast with different lengths are tested, the mode frequencies and mode shapes are compared with finite element model. The mode shapes match well with each other, while the frequencies tested by experiments are lower than the results of the finite element model, which reflects the joints lower the mast stiffness. The nonlinear dynamic characteristics are presented in the dynamic responses of the mast under different excitation force levels. The joint nonlinearities in the deployable mast are identified as nonlinear hysteresis contributed by the coulomb friction which soften the mast stiffness and lower the mast frequencies.

Nonlinear state estimation for fermentation process using cubature Kalman filter to incorporate delayed measurements

State estimation of biological process variables directly influences the performance of on-line monitoring and op- timal control for fermentation process. A novel nonlinear state estimation method for fermentation process is proposed using cubature Kalman filter （CKF） to incorporate delayed measurements. The square-root version of CI（F （SCKF） algorithm is given and the system with delayed measurements is described. On this basis, the sample-state augmentation method for the SCKF algorithm is provided and the implementation of the proposed algorithm is constructed. Then a nonlinear state space model for fermentation process is established and the SCKF algorithm incorporating delayed measurements based on fermentation process model is presented to implement the nonlinear state estimation. Finally, the proposed nonlinear state estimation methodology is applied to the state estimation for penicillin and industrial yeast fermentation processes. The simulation results show that the on-fine state estimation for fermentation process can be achieved by the proposed method with higher esti- mation accuracy and better stability.

Nonlinear System Identification Using Methods for Subspace

The identification of Wiener systems has been an active research topic for years. A Wiener system is a series connection of a linear dynamic system followed by a static nonlinearity. The difficulty in obtaining a representation of the Wiener model is the need to estimate the nonlinear function from the input and output data, without the intermediate signal availability. This paper presents a methodology for the nonlinear system identification of a Wiener type model, using methods for subspaces and polynomials of Chebyshev. The subspace methods used are MOESP （multivariable output-error state space） and N4SID （numerical algorithms for subspace state space system identification）. A simulated example is presented to compare the performance of these algorithms.

Kernelized fourth quantification theory for mineral target prediction

This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are ex- pected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quan- tifieation theory onto a low-dimensional scaling space, where the sealed cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the sealed cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly ceils. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional sealing space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model.

房地产与地方政府债务风险叠加机制及其金融空间溢出效应

房地产风险和地方政府债务风险通过空间关联和空间外溢作用向金融系统传递,如果任其在金融系统中隐性蔓延将酿成系统性金融风险。文章通过构建空间半参数非线性Durbin模型,对中国房地产风险、地方政府债务风险及其叠加机制的路径依赖和空间外溢效应进行分析。研究发现,房地产与地方政府债务风险对金融系统存在倒逼效应;房地产与地方政府债务风险的叠加也对金融系统产生负向的空间溢出效应。因此,防范和治理系统性金融风险,需要考虑房地产与地方政府债务风险叠加所产生的空间外溢效应,严格清理其风险空间外溢的路径"通道",重点强化房地产价格与地方政府债务融资的市场化机制。

基于改进无迹卡尔曼滤波的波动率研究

波动率估计是金融学的核心,波动几乎渗透金融市场的每一个领域.为了快速而精确地提取波动率,文章将比例UT变换与最小偏度单行采样技术和无迹卡尔曼滤波(UKF)算法相结合,提出一种适用于非线性高斯状态空间模型的改进的无迹卡尔曼滤波(MUKF)算法,并将该算法应用到扩散的期权定价模型中.最后通过对Heston随机波动模型进行模拟研究,发现在同时使用股票价格数据和期权数据时,可以精确地提取波动率,而且MUKF算法比UKF算法的计算时间更短.文章也对Heston模型中的波动率的波动参数进行了研究,研究发现MUKF算法可以准确地捕捉这种波动率特性.

挖掘机器人的系统建模与自动化控制——评《挖掘机器人系统建模、辨识与运动控制》

随着科技的进步,机器人技术逐渐被应用在工程机械领域,实现工程机械的智能化无人作业。严骏等编著的《挖掘机器人系统建模、辨识与运动控制》一书以挖掘机器人的高精度运动控制为目的展开研究。该书首先对挖掘机器人的相关技术以及研究现状、意义等做了简单阐述;接着建立了挖掘机器人试验样机电液伺服系统的分段线性模型和非线性状态空间模型,并对挖掘机器人电液伺服系统进行辨识研究,为控制仿真提供了参考模型;然后建立了挖掘机臂的运动学与动力学模型。

The Moduli Space in the Gauged Linear Sigma Model

This is a survey article for the mathematical theory of Witten's Gauged Linear Sigma Model, as developed recently by the authors. Instead of developing the theory in the most general setting, in this paper the authors focus on the description of the moduli.