To mirror and use LVM without VERITAS, you would have to bring these filesystems under the control of SVM.
要在不使用VERITAS的情况下镜像和使用LVM，就必须让这些文件系统受s VM控制。
Simulations demonstrate that SVM has good nonlinear approximation capability for inverse model, and the proposed control system has good dynamic and static performances as well as good robustness.
仿真研究表明，SVM具有优良的逆模型辨识能力，基于模糊控制补偿的支持向量机逆控制系统的动态性能好、跟踪精度高、鲁棒稳定性强。
SVM were used to identify the inverse model of nonlinear system, and this inverse model was used as feed-forward controller to design direct inverse control.
由SVM辨识非线性系统的逆模型作为前馈控制器，形成直接逆控制。
SVM has been applied to many fields such as pattern recognition, data mining, modeling and control of nonlinear system due to good generalization ability and globally optimal performance.
SVM由于其良好的泛化能力和全局最优性能，在模式识别、数据挖掘、非线性系统建模和控制等领域中展现出广泛的应用前景。
A new direct torque control (DTC) strategy of induction motors based on fuzzy space vector modulation (SVM) technology was proposed.
提出了一种基于模糊空间矢量调制(SVM)技术的异步电机直接转矩控制(DTC)方案。
Based on the thought of inverse system control, a composite strategy was proposed, which combines direct inverse control based on support vector machine (SVM) with PID control.
基于逆系统控制思想，提出一种支持向量机(SVM)直接逆控制与PID控制相结合的复合控制策略。
The AC-AC direct transformation control and the double-space-vector PWM scheme of the matrix converter are deduced, mathematic model of space vector modulation (SVM) matrix converter is built.
导出了矩阵变换器的交-交直接变换控制规律和双空间矢量PWM调制策略，建立了交-交直接变换控制方式下矩阵变换器的数学模型。
The simulation shows that the SVM model is highly reliable, it offers very important applicable values to implement realtime online control and online prediction for linear reciprocating generator.
仿真表明，SVM模型可靠高效，对实现直线振动发电机的实时在线控制及在线预测具有非常重要的应用价值。
An adaptive inverse control method based on Least Squares support vector machine (LS-SVM) is studied in this paper.
本文主要针对基于最小二乘支持向量机的自适应逆控制方法进行了研究。
Space vector modulation (SVM) is applied to the scheme, and decoupling control for the active and reactive power during the dynamic course is realized.
该方法基于空间电压矢量调制，实现了动态过程中有功功率和无功功率的解耦控制。
A nonlinear predictive control algorithm based on least squares support vector machines (LS-SVM) model was proposed.
提出一种基于最小二乘支持向量机(LS - SVM)的非线性系统预测控制算法。
This paper presents an approximate internal model control approach for unknown nonlinear discrete SISO systems based on the support vector machine(SVM).
该文对于未知非线性离散单输入单输出（SISO）系统提出了一种基于支持向量机的内模控制方法。
The model of the nonlinear system is obtained by LS-SVM, the offline model is linearize at each sampling instant and uses linear predictive function control methods to obtain the control law.
该算法采用LS-SVM回归建立非线性系统的预测模型，然后，将离线模型在每个采样周期关于当前采样点进行线性化，同时利用线性预测函数控制方法求解解析的控制律。
Model predictive control with least squares support vector machine (LS-SVM) has good control performance on the ship course even under the condition of disturbance and model parameter perturbation.
基于最小二乘支持向量机的船舶航向预测控制系统对外界干扰及模型参数摄动均具有较好的适应能力以及良好的控制性能。
Aiming at the pattern recognition of traffic flows in elevator group control systems, a method based on the multi-value classification SVM (Support Vector Machine) is put forward.
针对电梯群控调度中的交通流模式识别问题，提出了一种基于多值分类支持向量机的电梯交通流模式识别方法。
Aiming at the pattern recognition of traffic flows in elevator group control systems, a method based on the multi-value classification SVM (Support Vector Machine) is put forward.
针对电梯群控调度中的交通流模式识别问题，提出了一种基于多值分类支持向量机的电梯交通流模式识别方法。
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