基于UEGO的柴油机EGR系统的模型辨识

由于EGR系统存在严重的非线性、较大的时延和复杂的进排气动力特性，为了达到满意的控制效果，用伪随机二进制信号对系统进行了辨识。在大量预试验的基础上，对具有代表性的2种工况进行了系统辨识，得到了受控的自回归模型。模型降阶后得到2个具有时延的2阶模型。用交叉检验法检验了模型，检验结果表明模型完全可用于控制器的设计。     

煤层气发动机稳态空燃比前馈控制脉谱生成

基于煤层气发动机进气系统的物理特性,采用平均值、多项式和模糊神经网络建模方法,建立了用于稳态空燃比前馈控制的递阶模型,并通过该模型生成了三维初始控制脉谱图.借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型,进行了静态空燃比前馈控制仿真.利用前馈控制模型生成的数据,检验了实际控制效果.结果表明,前馈控制模型具有良好的预测能力,模型最大和平均预测误差分别小于8%和5%.     

液压盘式制动器模型试验

设计了通过测量制动臂所受的弯矩间接获得制动力矩的实车制动试验,采用系统辨识法获得制动力矩系数,得到盘式制动器试验模型.首先对应变电压-制动力矩的关系进行标定,然后实车测试不同制动工况下的制动力矩.根据实车试验得到制动压力,采用系统辨识的方法获得车辆制动压力-制动力矩的传递函数.试验结果表明,前、后轮的液压-制动力矩关系式可适用于不同工况下的制动力矩计算;制动器理论模型和试验模型的增益系数基本相符,但试验模型具有一阶惯性环节,更能准确地反映实际车辆的制动压力-制动力矩之间的关系.     

非线性时变系统的辨识方法的研究

传统控制系统的被控对象多是考虑到线性时不变系统,由于工业的高速发展,控制系统面临着巨大的变化,被控对象呈现出非线性、时变、时延和外界干扰的系统,并且系统的模型不容易被确定,因此人们首先必须对系统进行辨识,确定系统的模型,才能进行有效地控制。文章主要对辨识的方法进行研究,然后给出辨识的方法和步骤,最后辨识的仿真结果。     

锂电池分数阶等效电路模型的对比研究

为了分析模型误差对电池荷电状态估计的影响,以某三元锂电池为研究对象,对分数阶与整数阶的电池等效电路模型进行了比较分析。运用粒子群算法对模型进行参数辨识,进一步利用分数阶卡尔曼滤波算法实现电池的SOC估计,并与基于整数阶电池模型的SOC估计进行比较。实验结果表明,分数阶电池模型相较于整数阶模型具有更高的精度。     

考虑非线性摩擦模型的机器人动力学参数辨识

针对机器人动力学参数辨识的问题,提出了一种基于人工蜂群算法的辨识方法。考虑到关节摩擦特性,引入非线性摩擦模型,推导了机器人动力学模型的非线性形式。设计满足速度、加速度边界条件的五阶傅里叶级数作为激励轨迹来采集实验数据;利用人工蜂群算法,以蜂群为搜索单位,通过群体间的信息交流方式与优胜劣汰机制,对模型中的未知参数进行了辨识。最后,对得到的辨识模型进行了分析与验证,结果表明通过辨识得到关节预测力矩与测量力矩有较高的匹配度,所建立的非线性模型能够更好地描述机器人的动力学特性。     

4LYZ-2油菜收获机割台框架有限元模态分析

用Solidworks建立了4LZ-2型联合收获机割台框架和改装后的4LYZ-2型油菜联合收获机割台框架的三维模型;用ANSYS软件进行网格划分得到有限元模型,通过模态分析,得到了改装前后割台框架的前10阶固有频率和主振型。通过模态参数的分析,了解割台框架的振动情况以检验4LYZ-2型油菜联合收获机割台改装的合理性。     

异步电动机调速系统自适应辨识的CMAC-ADRC算法

针对异步电动机调速系统快速响应时启动超调量大的问题,提出了一种基于自适应参数辨识的小脑模型神经网络复合自抗扰控制(CMAC-ADRC)的控制算法。将CMAC与ADRC各自的优点相结合,利用CMAC神经网络实现前馈控制,通过在线学习来抑制系统的超调量,增强系统的鲁棒性能,提高系统的快速性能,利用ADRC技术实现反馈控制,进一步增强系统的抗干扰能力。利用参考模型自适应参数辨识技术对转动惯量进行辨识,优化自抗扰补偿系数。以变频器结合异步电动机为控制对象,进行仿真,基于自适应参数辨识的CMAC-ADRC控制算法的干扰响应幅度是一阶优化自抗扰控制下干扰响应幅度的44.57%,是小脑模型神经网络复合比例-微分(CMACPD)控制下干扰响应幅度的17.69%,干扰恢复时间是一阶优化自抗扰控制下干扰恢复时间的50%,是CMAC-PD控制下恢复时间的60%。搭建MCU-CPLD-DSP控制平台进行了实验,基于自适应参数辨识的CMAC-ADRC控制算法的超调量是一阶优化自抗扰控制的45.49%,上升时间是一阶优化自抗扰控制的53.33%,干扰响应幅度是一阶优化自抗扰控制干扰响应幅度的71%,干扰恢复时间是一阶优化自抗扰控制干扰恢复时间的76.47%。     

具有引导变量的模型在月平均气温预报中的应用

多层递阶方法包括多层递阶辨识、多层递阶预报和多层递阶控制。多层递阶预报方法已经成为我国长期和超长期天气预报10大主要方法之一。为此,应用了具有引导变量的模型的多层递阶预报模式,并对其进行了具体预报,预报的效果令人满意。     

汽车制动系统动态数学模型的辨识及有关问题研究

研究了建立汽车制动系统动态数学模型的方法和辨识动态模型的最优输入信号，提出了一种新的辨识制动系模型──方法相关广义最小二乘法（ＣＯＲ－ＧＬＳ），并对具体算法编制了快速高精度软件；进而以挂车分配阀为例，就此问题进行了深入研究，并得到了它的差分模型和传递函数．同时采用两种方式进行了模型验证，且对该模型的频响函数予以分析探讨，得出了评价汽车制动性能的新方法──频率响应函数法和制动因子理论，最后就采用用辨识理论优化汽车制动系统的有关问题进行了理论研究．     

Development of a mathematical model to study the impacts of production and management policies on the herd dynamics and profitability of dairy goats

The reduction in goat milk production and the competitiveness of more profitable activities have increased the adoption of measures to enhance goat milk and meat around the world. A simulation model was built to evaluate the dynamics of a dairy goat herd under different scenarios of production. A System Dynamics approach was used to identify management policies that could affect the behaviour of the herd over 10 years of simulation using data from a dairy goat herd in Brazil. The impact of reproductive and mortality rates, one or two annual reproductive cycles on production, and economic health of dairy goats on changes in the herd dynamics were evaluated. Simulations indicated that small changes in reproduction and mortality rates and milk price can considerably affect the dynamics of the herd as well as the financial health of the production system. The interferences created to visualize the effects were not immediately realized because of intrinsic delays in the system. The comparison of models with one or two breeding seasons indicated that the latter was considerably more profitable and had a faster turnover. It was also found that the two breeding season had a greater capacity to support reduction in milk price that could generate financial instability in the production system. It was concluded that mathematical models can be used to predict impacts in management policies on herd dynamics and sensitivity to support the dairy goat activity showing its viability as an agricultural activity that can contribute to the production and incomes in small farms.     

Application of the relevance vector machine to canal flow prediction in the Sevier River Basin

This work addresses management of water for irrigation in arid regions where significant delays between the time of order and the time of delivery present major difficulties. Motivated by improvements to water management that will be facilitated by an ability to predict water demand, it employs a data-driven approach to developing canal flow prediction models using the relevance vector machine (RVM), a probabilistic kernel-based learning machine. A search is performed across model attributes including input set, kernel scale parameter and model update scheme for models providing superior prediction capability using the RVM. Models are developed for two canals in the Sevier River Basin of southern Utah for prediction horizons of up to 5 days.     

三轴车辆转向性能分析

建立了多轴车辆定比例转向系统理想模型和多轴车辆侧向动力学模型,通过对两模型定比例转向时的低速转向半径进行比较,验证了多轴车辆侧向动力学模型的合理性.基于该模型,分别分析了定比例转向系统和变比例转向系统的低速转向半径和高速操纵稳定性.结果表明:定比例转向的多轴转向系统低速机动性不够好,且高速稳定性很差;变比例转向的多轴转向系统在提高车辆机动性的同时,还能改善车辆的高速稳定性.     

基于减振器阻尼非线性的汽车悬架系统建模与研究

在进行汽车悬架系统建模时,把减振器建立成线性与非线性两种模型,从而建立相应的两种悬架模型,并运用平均加速度法对这两种模型进行推导求解。在求解过程中运用Matlab中的S-函数构建仿真模块。仿真与试验数据的对比结果表明,选用合适的非线性减振器模型比采用线性模型更符合实际,更利于对汽车平顺性的研究。     

Frame-based modelling as a method of simulating rangeland production systems in the long term

Rangelands are complex systems with many interacting components. Modelling such systems presents two particular and interrelated problems. Firstly, the processes involved operate on greatly differing time scales: long-term changes in rangelands typically depend on much shorter-term processes such as rainfall, vegetation growth and livestock growth. Secondly, while complex mechanistic models of single animals or small herds have been developed (also involving differing time scales, from minutes to months), extending such models to an entire multi-species rangeland is generally an intractable problem. Recently, a new modelling paradigm has been introduced which facilitates the building of ‘economical’ systems models by using the concept of a frame. Frames are chosen to represent distinct states of the system (e.g. grassland with scattered mature trees, as opposed to dense bush cover). Independent models are constructed for each frame; these models simulate the key processes identified within that frame (and may themselves be simplifications of more complex models). Rules are established for switching frames. In this paper we describe a frame-based model of a typical Southern African rangeland supporting cattle and goats. Simple quantitative models for each frame are developed from the output of a complex mechanistic model, depending on rainfall, stocking density and animal condition. Results from the overall frames model show how long-term responses of the system (in terms of production and vegetation state) to various management strategies (such as livestock sales) may be predicted, and in this way allows comparison of different management strategies.     

A generalised model of feed intake and digestion in lactating cows

A generalised dynamic model for estimating voluntary consumption and digestion of feed by lactating dairy cows is described. Feed intake is assumed to be regulated either by metabolic factors relating energy intake to energy expenditure, or by physical factors associated with the capacity of the rumen to hold feed cell wall components. A representation of rumen function defined on an hourly basis provides estimates of digestion and passage of cell wall, and of the quantity of residue remaining in the rumen prior to the next meal from which physical intake limitations are calculated. Changes in regulation of energy intake and in maximum rumen capacity in response to changes in energy expenditure are subject to adjustment delays and are recalculated daily.Both qualitatively and quantitatively the model behaves well with respect to interactions between rumen function and short-term regulatory mechanisms over a wide range of feedstuffs. However, the dynamics of model behaviour over the long term-one lactation-indicate a systematic error in estimating changes in feed intake which is particularly evident in early lactation. The main cause of this error is thought to involve inadequacies in the representation of adjustment delays in the regulatory system.     

温室测控系统开关设备优化组合预测控制方法

考虑开关设备组合作用下温室测控系统的非线性动态特性,提出了结构简单、不需复杂数值计算的离散预测模型,在不小于最大时滞时域内设备组合不变情况下,对设备组合进行滚动优化预测控制,从而大大简化了温室测控系统预测控制算法的复杂性,缓解了测控系统分布大时滞问题。仿真分析和温度的均方差表明,对分布式、大时延温室测控系统的优化组合预测控制方法是有效的。     

Using automated monitoring systems to uncover pest population dynamics in agricultural fields

Understanding pest population dynamics is an essential part of pest management programs, but the examination of field pest populations faces many logistical difficulties. Consequently, potentially useful characteristics of pest ecology that can be utilized in the development of pest control strategies are yet to be discovered. In this study, we used an automated pest monitoring system to study a population of the oriental fruit fly and revealed its intriguing population dynamics in the field. The system automatically counts the number of flies captured by traps, and the real-time data are accessible anywhere using the Internet. Data from two time periods (May–June and July–August) were analyzed. Autocorrelation analysis indicated that there was a statistically significant population cycle in May and June, but the population was stationary in July and August. Partial rate correlation analysis and an associated functional analysis revealed the existence of delayed density-dependence that differed between the two periods. These results suggest that the mechanism of population dynamics may change possibly within a short time frame. These patterns were revealed because of the detailed data that were made available by the monitoring system and were unknown prior to the study. The automated monitoring system will be highly valuable for the advancement of pest monitoring and pest management programs.     

车辆传动系统虚拟样机建模与验证

为实现在设计阶段对车辆传动系统性能进行预测,以目前广泛应用的液力机械传动系统的组成和工作原理为基础,提出了可闭锁式液力变矩器和换挡离合器两个关键部件级,以及整个系统级虚拟样机建模方法,并进一步分析建立了相对应的数学模型。以起步工况试验的动力输入特性和操纵方式作为模型的输入条件对其进行了验证。通过仿真与试验测试结果对比,表明所建立的模型正确、合理并具有较高的精度。     

节水灌溉条件下宁夏银北灌区地下

根据灌区引水、排水、降水及蒸发等长观资料，分析讨论了宁夏银北引黄灌区大气降水、地表水、地下水相互转化规律及其时空分布状况。采用有限元法，建立了银北灌区地下水动态数值模型。在此基础上，研究了采取节水灌溉措施后，灌区地下水动态。首先按照优化后的灌区作物种植结构及相应的灌溉定额，反推灌区灌溉引水量。然后，通过相关分析，得到与灌溉引水量相对应的沟排量。最后，用反推所得数据及典型年份的降水和蒸发资料，进行了地下水动态趋势分析和数值模拟计算，给出了模型的预测结果，并将预测结果绘制成相应的地下水等水位线图。