多传感器量测自适应Rao-Blackwellised粒子滤波算法

针对量测不确定下非线性系统状态估计中多传感器量测数据的有效利用和计算复杂度的简化问题,给出了一种多传感器量测自适应Rao-Blackwellised粒子滤波算法。首先,通过随机采样策略和量测模型先验转移概率实现用于评估粒子权重的传感器有效量测集合的采样;其次,利用重采样步骤和概率最大化原则完成对不含扰动影响传感器量测模型的辨识;最终,依据Rao-Blackwellised粒子滤波中非线性状态分量和线性状态分量的独立求解方式实现当前时刻系统的状态估计。理论分析和仿真实验结果验证了算法的可行性和有效性。     

基于正交模型辨识辅助的欠采样数字预失真方法

针对数字预失真技术在宽带通信系统中的具体实现受到模数转换器采样率制约的问题,提出一种新的欠采样数字预失真方法。首先在欠采样速率下对功放的正交模型进行离线辨识,接着根据一定的算法得到Nyquist采样率下的简化预失真器模型,并进行在线的自适应直接学习。该方法具有预失真器模型构造简单、欠采样实现高效的特点。理论分析和仿真结果表明,该方法有效降低了对模数转换器的采样率要求,优化了简化预失真器模型的线性化条件,更好地抑制了功放非线性引起的带内失真和频谱再生。     

非线性微分-代数系统稳定性的几个判据

研究非线性微分－代数系统的稳定性问题,给出利用非线性函数的偏导数矩阵判别非线性微分－代数系统平衡态稳定和不稳定的几个判据,所得结果形式简洁,易于应用．最后利用例子说明所得判据的有效性     

The Fuzzy Control Forecast of Fully-|Mechanized Coal Face Production Capacity

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The Blowing-up of the Solutions for a Class of Nonlinear Reaction-Diffusion Equations

Wediscusstheblowing-upofthesolutionsforthenonlinearreaction-diffusionequationswiththegeneral(i.e.nonlinear)boundaryconditions:ut=∑ni,j=1xiaij(x)uxj ∑ni=1bi(x)uxi f(u)　(x,t)∈Ω×(0,T)βuγ δ(x)uΩ=g(u)u(x,0)=u0(x)(*)whereΩisaboundedregionofRn,ai...     

A MULTISTEP CHARACTERISTIC FINITE DIFFERENCE METHOD FOR TWO-DIMENSIONAL NONLINEAR CONVECTION-DIFFUSION PROBLEMS

1.IntroductionItiswellknowthattheconvection-dictionproblemsareakindofveryimportalprob-lems,particularlylthenonlinearconvection-diffusionproblexns.Inthepaper[1],asinglestepcharacteristicflutedmerencemethodisgivenforsolvingtwcadimensionalnonlinearconvection-dilhaionproblemswiththeconvectivecoefficientsdominating.HereweshallgiveamultistepcharactersticamrencemethodbasedonthelinearandquadraticinterpolationsforsolvingtwcadAnensionalnonlinearconvection-~ionproblemsinordertoincreasetheaccuracyofapprot…     

A SINGLESTEP CHARACTERISTIC FINITE DIFFERENCE METHOD FOR TWO-DIMENSIONAL NONLINEAR CONVECTION-DIFFUSION PROBLEMS

1.IntroductionThenonlinearconvection-diffusionproblemsareakindofveryimportantproblemssuchastheundergroundpercolation,air--pollution,fluidmechanicsmodelingetc.Thenumericalmethodsforsolvingthelinearproblemswiththeconvectivecoefficientsdominating,whicharethecharacteristicfiniteelementandcharacteristicfinitedifferencemethods,aregivenbyJ.DouglasandT.F.Russellin[1]andfurtherdevelopmentin[2]and[3],etc.ButtheconvergenceofmethodsneedstherestrictiveassumptionAt=O(h).Inpracticeonewouldliketotakebigger…     

Robust H∞ control for neutral stochastic uncertain systems with time-varying delay

The problem of robust H∞ control for uncertain neutral stochastic systems with time-varying delay is discussed. The parameter uncertaintie is assumed to be time varying norm-bounded. First, the stochastic robust stabilization of the stochastic system without disturbance input is investigated by nonlinear matrix inequality method. Then, a full-order stochastic dynamic output feedback controller is designed by solving a bilinear matrix inequality (BMI), which ensures a prescribed stochastic robust H∞ performance level for the resulting closed loop system with nonzero disturbance input and for all admissible uncertainties. An illustrative example is provided to show the feasibility of the controller and the potential of the proposed technique.     

非线性微分〖CDF*2〗代数系统的自适应状态观测器设计

针对非线性微分-代数系统,给出了可观性判据,提出了基于非线性微分-代数方程的自适应状态观测器设计方法。根据状态观测器工作点变化在线配置极点,获得合适的观测器的反馈增益阵,保证观测器在大范围内稳定工作。理论分析了存在模型误差时观测器的鲁棒性,证明如果模型稳态无差,观测器也是稳态无差的。以化工过程中的典型微分-代数系统为例,仿真结果证明了用该方法设计的观测器能够稳定收敛到状态真值,具有较好的动态性能。     

非线性非高斯模型的高斯和滤波算法

通过将模型的状态噪声和观测噪声均表示成高斯和的形式,推导出非线性非高斯状态空间模型的高斯和递推算法,进一步提出了对应的扩展卡尔曼和滤波器（extended Kalman sum filter, EKSF）和高斯厄密特和滤波器（Gauss-Hermite sum filter, GHSF）。EKSF和GHSF分别用扩展卡尔曼滤波器（extended Kalman filter, EKF）和高斯厄密特滤波器（Gauss-Hermite filter, GHF）作为高斯子滤波器。分析的结果表明,现有的高斯和滤波算法是本文算法的特例;仿真结果表明,EKSF和GHSF能有效处理非线性非高斯模型的状态滤波问题,与高斯和粒子滤波器（Gaussian sum particle filter, GSPF）相比,EKSF和GHSF在保证精度的同时,大大降低了计算量,仿真时间分别约为GSPF的5%和6%。