ID 原文 译文
14305 复合辨识方案根据数据的分布信息,利用加权LS-SVM对异常数据的鲁棒性,通过回归计算消除数据的异常性。 According tothe distribution information of the data and by use of the robustness of weighted LS-SVM to abnormal data the identification scheme removes anomalism of the data through regression calculation．
14306 再利用预处理后的数据训练补偿模糊神经网络参数,得到系统模型。 Furthermore the preprocessed data is used for data training to compensate for parameters of the fuzzy neural network and thesystem model is obtained．
14307 结果表明,采用加权LS-SVM预处理的复合辨识方案运用在普遍存在随机噪声的系统中,能获得更加准确的辨识模型。 The proposed composite identification scheme behaves better in the simulation ofsystem identification with random noise．
14308 针对刚性机械臂有限时间鲁棒控制问题,提出了一种新的自适应非奇异快速终端滑模控制方法。 For the finite-time robust control of a rigid robot manipulator a new adaptive non-singular fastterminal sliding mode control method is proposed．
14309 该方法将非奇异快速终端滑模控制与自适应律相结合,使用非奇异快速终端滑模面加快机械臂轨迹跟踪误差的收敛速度,解决了终端滑模中的奇异问题。 This method combines non-singular fast terminal slidingmode control with adaptive law． Firstly, the non-singular fast terminal sliding surface is selected which isused to accelerate the convergence rate of trajectory tracking error of manipulator and solve singularproblems in terminal sliding surface．
14310 通过双曲正切函数代替符号函数减小控制输入的抖振；利用自适应律对未知的外部扰动和系统的不确定性进行估计,实现了在集总扰动未知情况下的轨迹跟踪。 Then, hyperbolic tangent function replaces sign function to reducechattering of control input． Moreover, the adaptive law estimates the unknown external disturbance anduncertainties, so as to achieve trajectory tracking with unknown lumped disturbance．
14311 构造Lyapunov函数,证明机械臂系统能够在有限时间内稳定收敛。 It is proved that therobot manipulator system can converge stably in finite time by establishing the Lyapunov function.
14312 最后二自由度机械臂仿真实验结果验证了所设计控制器的有效性和鲁棒性。 Finally,the simulation results of a two-DOF robot manipulator are presented to illustrate the effectiveness androbustness of the proposed control method．
14313 针对海杂波背景下漂浮小目标检测问题,提出一种海杂波背景下漂浮小目标检测新算法。 Aiming at the problem of floating small target detection under sea clutter background a newfloating small target detection algorithm EEMDCAN-Ｒobust ICA ＆ SG is proposed．
14314 利用互补自适应噪声集合经验模式分解-鲁棒性独立主成分分析与Savitzky-Golay滤波算法(EEMDCAN-Robust ICA&SG)联合去噪算法处理海面回波信号,对重构信号用改进蝙蝠算法优化KELM模型做混沌预测。 The denoising algorithmcombines EEMDCAN Ｒobust ICA with Savitzky-Golay filtering algorithm to process sea echo signal and theimproved bat algorithm is used to optimize KELM model for chaotic prediction of reconstructed signal．