A novel strategy of probability density function （PDF） shape control is proposed in stochastic systems. The control er is designed whose parameters are optimal y obtained through the improved particle swarm optimiza...A novel strategy of probability density function （PDF） shape control is proposed in stochastic systems. The control er is designed whose parameters are optimal y obtained through the improved particle swarm optimization algorithm. The parameters of the control er are viewed as the space position of a particle in particle swarm optimization algorithm and updated continual y until the control er makes the PDF of the state variable as close as possible to the expected PDF. The proposed PDF shape control technique is compared with the equivalent linearization technique through simulation experiments. The results show the superiority and the effectiveness of the proposed method. The control er is excellent in making the state PDF fol ow the expected PDF and has the very smal error between the state PDF and the expected PDF, solving the control problem of the PDF shape in stochastic systems effectively.展开更多
This paper presents a new algorithm designed to control the shape of the output probability density function (PDF) of singular systems subjected to non-Gaussian input. The aim is to select a control input uk such that...This paper presents a new algorithm designed to control the shape of the output probability density function (PDF) of singular systems subjected to non-Gaussian input. The aim is to select a control input uk such that the output PDF is made as close as possible to a given PDF.Based on the B-spline neural network approximation of the output PDF, the control algorithm is formulated by extending the developed PDF control strategies of non-singular systems to singular systems. It has been shown that under certain conditions the stability of the closed-loop system can be guaranteed. Simulation examples are given to show the effectiveness of the proposed control algorithm.展开更多
A predictive control strategy is proposed for the shaping of the output probability density function (PDF) of linear stochastic systems. The B-spline neural network is used to set up the output PDF model and therefore...A predictive control strategy is proposed for the shaping of the output probability density function (PDF) of linear stochastic systems. The B-spline neural network is used to set up the output PDF model and therefore converts the PDF-shaping into the control of B-spline weights vector. The Diophantine equation is then introduced to formulate the predictive PDF model, based on which a moving-horizon control algorithm is developed so as to realize the predictive PDF tracking performance.展开更多
A new fault tolerant control（FTC） via a controller reconfiguration approach for general stochastic nonlinear systems is studied.Different from the formulation of classical FTC methods,it is supposed that the measure...A new fault tolerant control（FTC） via a controller reconfiguration approach for general stochastic nonlinear systems is studied.Different from the formulation of classical FTC methods,it is supposed that the measured information for the FTC is the probability density functions（PDFs） of the system output rather than its measured value.A radial basis functions（RBFs） neural network technique is proposed so that the output PDFs can be formulated in terms of the dynamic weighings of the RBFs neural network.As a result,the nonlinear FTC problem subject to dynamic relation between the input and the output PDFs can be transformed into a nonlinear FTC problem subject to dynamic relation between the control input and the weights of the RBFs neural network approximation to the output PDFs.The FTC design consists of two steps.The first step is fault detection and diagnosis（FDD）,which can produce an alarm when there is a fault in the system and also locate which component has a fault.The second step is to adapt the controller to the faulty case so that the system is able to achieve its target.A linear matrix inequality（LMI） based feasible FTC method is applied such that the fault can be detected and diagnosed.An illustrated example is included to demonstrate the efficiency of the proposed algorithm,and satisfactory results have been obtained.展开更多
混煤燃烧存在复杂的相互影响,将混煤当成单一煤种并采用单混合分数/概率密度函数(probability density function,PDF)方法计算,意味着忽略了煤种之间的影响,结果会产生很大偏差。而双混合分数/PDF方法可以分别定义各单煤性质并跟踪各单...混煤燃烧存在复杂的相互影响,将混煤当成单一煤种并采用单混合分数/概率密度函数(probability density function,PDF)方法计算,意味着忽略了煤种之间的影响,结果会产生很大偏差。而双混合分数/PDF方法可以分别定义各单煤性质并跟踪各单煤的燃烧过程,能够体现煤种之间燃烧特性的影响。利用单、双混合分数/PDF方法对同1台300 MW四角切圆锅炉进行模拟研究,并与实测数据进行对比,结果表明:双混合分数/PDF方法模拟的结果更符合混煤在炉内实际的燃烧情况。同时采用双混合分数/PDF方法模拟某一混煤燃烧过程,得到燃烧煤粉锅炉的流动,温度和烟气分布等特性。展开更多
针对海上风力发电机组高转速叶轮对风机结构会造成强烈的周期性激励,而该强谐波作用往往会淹没响应中的结构模态信息,增加识别结构工作模态参数难度问题,以某海上风电试验样机振动响应原型观测信号为研究对象,采用基于改进特征系统实现...针对海上风力发电机组高转速叶轮对风机结构会造成强烈的周期性激励,而该强谐波作用往往会淹没响应中的结构模态信息,增加识别结构工作模态参数难度问题,以某海上风电试验样机振动响应原型观测信号为研究对象,采用基于改进特征系统实现法(Eigensystem Realization Algorithm,ERA)与概率密度函数法(Probability Density Function,PDF)结合的工作模态识别方法及判定思路,剔除不同工况下转频、倍频谐波成分干扰,实现风机结构多阶工作模态参数有效识别。该方法不仅能有效避免谐波干扰以获取结构的真实工作模态,同时对海上风机结构运行安全性实时在线监测、评估具有较好的工程适用性。展开更多
基金supported by the National Natural Science Fundation of China(61273127)the Specialized Research Fund of the Doctoral Program in Higher Education(20106118110009+2 种基金20116118110008)the Scientific Research Plan Projects of Shaanxi Education Department(12JK0524)the Young Teachers Scientific Research Fund of Xi’an University of Posts and Telecommunications(1100434)
文摘A novel strategy of probability density function （PDF） shape control is proposed in stochastic systems. The control er is designed whose parameters are optimal y obtained through the improved particle swarm optimization algorithm. The parameters of the control er are viewed as the space position of a particle in particle swarm optimization algorithm and updated continual y until the control er makes the PDF of the state variable as close as possible to the expected PDF. The proposed PDF shape control technique is compared with the equivalent linearization technique through simulation experiments. The results show the superiority and the effectiveness of the proposed method. The control er is excellent in making the state PDF fol ow the expected PDF and has the very smal error between the state PDF and the expected PDF, solving the control problem of the PDF shape in stochastic systems effectively.
基金Supported by the Research Fund of Chinese Academy of Sciences (2004-1-4)
文摘This paper presents a new algorithm designed to control the shape of the output probability density function (PDF) of singular systems subjected to non-Gaussian input. The aim is to select a control input uk such that the output PDF is made as close as possible to a given PDF.Based on the B-spline neural network approximation of the output PDF, the control algorithm is formulated by extending the developed PDF control strategies of non-singular systems to singular systems. It has been shown that under certain conditions the stability of the closed-loop system can be guaranteed. Simulation examples are given to show the effectiveness of the proposed control algorithm.
基金Supported by National Natural Science Foundation of P. R. China (60128303)
文摘A predictive control strategy is proposed for the shaping of the output probability density function (PDF) of linear stochastic systems. The B-spline neural network is used to set up the output PDF model and therefore converts the PDF-shaping into the control of B-spline weights vector. The Diophantine equation is then introduced to formulate the predictive PDF model, based on which a moving-horizon control algorithm is developed so as to realize the predictive PDF tracking performance.
文摘间歇过程的优化控制依赖于过程精确的数学模型,数据驱动的建模方法是目前间歇过程模型研究中的热点问题。突破传统数据驱动建模方法中采用均方差(mean squared error,MSE)作为准则函数的思想,提出一种新颖的间歇过程数据驱动建模方法,引入了概率密度函数(probability density function,PDF)控制的概念,构造间歇过程模型误差控制系统,将模型的可调参数作为控制系统的输入,模型误差PDF的形状作为控制系统的输出,从而把开环模型参数辨识问题转化为模型误差PDF形状的闭环控制问题。通过可调参数控制模型误差PDF的空间分布状态,不仅能够保障模型精度,还可控制模型误差的空间分布状态,从而消除模型中的有色噪声。仿真实验表明,基于模型误差PDF形状的间歇过程数据驱动模型具有较好的建模精度、鲁棒性和泛化能力,为间歇过程的数据驱动建模提供了一条新途径。
基金supported by the UK Leverhulme Trust (F/00 120/BC)the National Natural Science Foundation of China (6082800760974029)
文摘A new fault tolerant control（FTC） via a controller reconfiguration approach for general stochastic nonlinear systems is studied.Different from the formulation of classical FTC methods,it is supposed that the measured information for the FTC is the probability density functions（PDFs） of the system output rather than its measured value.A radial basis functions（RBFs） neural network technique is proposed so that the output PDFs can be formulated in terms of the dynamic weighings of the RBFs neural network.As a result,the nonlinear FTC problem subject to dynamic relation between the input and the output PDFs can be transformed into a nonlinear FTC problem subject to dynamic relation between the control input and the weights of the RBFs neural network approximation to the output PDFs.The FTC design consists of two steps.The first step is fault detection and diagnosis（FDD）,which can produce an alarm when there is a fault in the system and also locate which component has a fault.The second step is to adapt the controller to the faulty case so that the system is able to achieve its target.A linear matrix inequality（LMI） based feasible FTC method is applied such that the fault can be detected and diagnosed.An illustrated example is included to demonstrate the efficiency of the proposed algorithm,and satisfactory results have been obtained.
文摘混煤燃烧存在复杂的相互影响,将混煤当成单一煤种并采用单混合分数/概率密度函数(probability density function,PDF)方法计算,意味着忽略了煤种之间的影响,结果会产生很大偏差。而双混合分数/PDF方法可以分别定义各单煤性质并跟踪各单煤的燃烧过程,能够体现煤种之间燃烧特性的影响。利用单、双混合分数/PDF方法对同1台300 MW四角切圆锅炉进行模拟研究,并与实测数据进行对比,结果表明:双混合分数/PDF方法模拟的结果更符合混煤在炉内实际的燃烧情况。同时采用双混合分数/PDF方法模拟某一混煤燃烧过程,得到燃烧煤粉锅炉的流动,温度和烟气分布等特性。
文摘针对海上风力发电机组高转速叶轮对风机结构会造成强烈的周期性激励,而该强谐波作用往往会淹没响应中的结构模态信息,增加识别结构工作模态参数难度问题,以某海上风电试验样机振动响应原型观测信号为研究对象,采用基于改进特征系统实现法(Eigensystem Realization Algorithm,ERA)与概率密度函数法(Probability Density Function,PDF)结合的工作模态识别方法及判定思路,剔除不同工况下转频、倍频谐波成分干扰,实现风机结构多阶工作模态参数有效识别。该方法不仅能有效避免谐波干扰以获取结构的真实工作模态,同时对海上风机结构运行安全性实时在线监测、评估具有较好的工程适用性。
