共查询到18条相似文献,搜索用时 47 毫秒
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本文研究倒立摆的控制器设计.运用控制转换定律和Lyapunov第二方法,有效解决了由钟的分离角和控制系统中小车的置换引起的强非线性和强耦合性难题.并证明该控制器对由摆的长度和质量以及小车的质量等参数决定的非线性摩擦系数的变化具有强鲁棒性.最后,仿真实验结果证明了该控制器设计的可行性. 相似文献
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微分对策求解往往涉及到困难的两点边值问题(TPBV),将线性二次型微分对策问题归结于Hamilton体系.对Hamilton系统,辛几何算法具有能复制Hamilton系统的动态结构并保持相平面上的测度的优点.从Hamilton系统角度,探讨了线性二次型微分对策系统的辛性质;作为尝试,对无限期间线性二次型微分对策的计算引入Symplectic-Runge-Kutta算法.给出了一个数值计算实例,从结果可以说明这种方法的可行,也体现了辛算法对系统的能量具有良好的守恒性. 相似文献
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1引言众所周知,某些复杂的工业过程用线性近似动态模型是不适宜的,而且许多对象如工业生产,生态,生物和社会经济等过程可以用双线性模型自然描述,能够在稳态工作点的一个较大领域内描述一大类严重非线性系统的动态特性,描述精度优于传统的线性模型 相似文献
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本文提出具有线性等式约束多目标规划问题的一个降维算法.当目标函数全是二次或线性但至少有一个二次型时,用线性加权法转化原问题为单目标二次规划,再用降维方法转化为求解一个线性方程组.若目标函数非上述情形,首先用线性加权法将原问题转化为具有线性等式约束的非线性规划,然后,对这一非线性规划的目标函数二次逼近,构成线性等式约束二次规划序列,用降维法求解,直到满足精度要求为止. 相似文献
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详细研究了一种一元非线性系统的BP算法,提出并证明了该算法的收敛性定理,给出了该算法的应用实例.计算机仿真结果表明:对于随机给定的初始点,该算法都能稳定收敛到它的一个实根,而且计算精度可控,因此,该算法是有效的.与传统的计算方法相比,本文算法不仅具有收敛速度快,而且计算精度可控以及初始点随机给定的集中优点. 相似文献
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应用Kleinman迭代算法,研究了一类非线性系统的在线自适应控制器设计问题.基于神经网络线性微分包含技术,对此类非线性系统进行建模描述.并在不利用系统后续参数矩阵的情况下,应用Kleinman迭代算法进行反复迭代,求解系统的Riccati方程.进而设计系统的自适应控制器,并证明了该算法的收敛性.最后通过数值仿真验证了该算法的可行性. 相似文献
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基于变换X=VV~T,本文将半定规划问题转换为非线性规划问题,提出了解决此问题的增广拉格朗日算法,并证明了算法的线性收敛性.在此算法中,每一次迭代计算的子问题利用最速下降搜索方向和满足wolf条件的线性搜索法求最优解.数值实验表明,此算法是行之有效的,且优于内点算法. 相似文献
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应用求解算子方程的Ulm方法构造了求解一类矩阵特征值反问题(IEP)的新算法.所给算法避免了文献[Aishima K.,A quadratically convergent algorithm based on matrix equations for inverse eigenvalue problems,Linear Algebra and its Applications,2018,542:310-33]中算法在每次迭代中要求解一个线性方程组的不足,证明了在给定谱数据互不相同的条件下所给算法具有根收敛意义下的二次收敛性.数值实验表明本文所给算法在矩阵阶数较大时计算效果优于上文所给算法. 相似文献
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针对小车平面运动n级倒立摆系统,利用Lagrange方程和刚体力学的一些理论,给出了模型建立过程,最后得到了平面运动n级倒立摆的统一数学模型. 相似文献
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许迅雷 《数学的实践与认识》2012,42(8):97-101
UKF作为一种新的非线性滤波方法已在目标跟踪问题中得到应用,在状态的时间更新阶段直接使用非线性模型,不引入线性化误差,而且不必计算Jacobians矩阵.提出了一种基于方根分解形式的带有衰减因子的UKF算法(SRDMA-UKF),算法的方根形式增加了数字稳定性和状态协方差的半正定性.通过衰减因子的引入加强对当前测量数据的利用,减小历史数据对滤波的影响.仿真实验结果表明,该算法与UKF算法相比具有更好的滤波性能. 相似文献
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A. Hermoso-Carazo J. Linares-Pérez 《Applied mathematics and computation》2011,217(20):7998-8009
An approximation to the least squares filter is proposed for discrete signals whose evolution is governed by nonlinear functions, when the estimation is based on nonlinear observations with additive noise which can consist only of random noise; this uncertainty in the observation process is modelled by Bernoulli random variables which are correlated at consecutive time instants and are otherwise independent. The proposed recursive approximation is based on the unscented principle; successive applications of the unscented transformation to a suitable augmented state vector enable us to approximate the one-stage state and observation predictors from the state filter at the previous time instant. The performance of the proposed algorithm is compared with that of an extended algorithm in a numerical simulation example. 相似文献
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An unscented filtering algorithm is derived for a class of nonlinear discrete-time stochastic systems using noisy observations which can be randomly delayed by one or two sample times. The update and the possible delays (of one and two sampling times) of any observation are modelled by using three Bernoulli random variables such that only one of them takes the value one. The algorithm performs in two-steps, prediction and update, and it uses a scaled unscented transformation to approximate the conditional mean and covariance of the state and observation at each time. The performance of the proposed filter is shown in a simulation example which uses a growth model with randomly delayed observations; in this example, the proposed filter is compared with the extended one obtained by linearizing the state and the observation equations and, also, with the unscented Kalman filter. A clear superiority of the proposed filter over the others is inferred. 相似文献
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In this paper, the least squares filtering problem is investigated for a class of nonlinear discrete-time stochastic systems using observations with stochastic delays contaminated by additive white noise. The delay is considered to be random and modelled by a binary white noise with values of zero or one; these values indicate that the measurement arrives on time or that it is delayed by one sampling time. Using two different approximations of the first and second-order statistics of a nonlinear transformation of a random vector, we propose two filtering algorithms; the first is based on linear approximations of the system equations and the second on approximations using the scaled unscented transformation. These algorithms generalize the extended and unscented Kalman filters to the case in which the arrival of measurements can be one-step delayed and, hence, the measurement available to estimate the state may not be up-to-date. The accuracy of the different approximations is also analyzed and the performance of the proposed algorithms is compared in a numerical simulation example. 相似文献
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Singular Points Near an X_0-breaking Double Singular Fold Point in Z_2-symmetric Nonlinear Equations
SingularPointsNearanX_0-breakingDoubleSingularFoldPointinZ_2-symmetricNonlinearEquationsSuYi(苏毅)andWuwei(吴微)(DepartmentofMathe... 相似文献
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给出了中心对称三次系统存在一类双纽线分界线环的充要条件,并举出此系统至少还存在四个极限环的(2.2)分布的例子.还举出了中心对称三次系统至少存在六个极限环作(3.3)分布以及五个极限环,其中一个极限环包围作(2.2)分布的四个极限环的例子. 相似文献