详细描述了非线性控制理论几何结构原理的精确线性化算法的过程。
In all details, this paper introduces the algorithmic procedure on the geometric structure principium of nonlinear control theory.
进而给出了材料参数已知时，摩擦系数识别非线性问题的一种线性化算法。
A kind of linearized algorithm is given out to identify the friction coefficient when the material parameters are known. Experiments show that the above algorithms are practicable.
对求解CTDM的部分线性化算法进行分析，提出了在进行步长优化时使用二次插值法得到模拟最优步长的方法。
By analyzing the partial linearization algorithm of CTDM, a quadratic interpolation method is proposed to obtain the approximated optimal step size.
采用SIMPLE算法，对计算方程进行线性化；
详细介绍温度、压力线性化的具体算法及实现步骤。
The concrete algorithms and implementing procedures of linearizations for temperature and pressure are introduced in detail.
因此我们针对死区非线性特性，采用非线性逆函数的全局I/O线性化方法，提出了具有非线性补偿的广义预测控制算法。
So with the wide I/O linearization method of nonlinear reverse function, the generalized prediction control algorithm with dead area nonlinear compensation is suggested.
针对非线性船舶航向保持系统，给出一种基于精确反馈线性化和闭环增益成形算法的非线性鲁棒pid控制器，该非线性PID控制器由非线性函数项和鲁棒pid控制器组成。
For a nonlinear course keeping system for ships, a kind of nonlinear robust PID is presented, which is based on an exact feedback linearization and a closed-loop gain shaping algorithm.
针对隐含着0 ~1要素、难以拟线性化的扒口分洪问题，提出了判断扒口分洪界点及其相应的分阶段算法的处理方法。
For solving blasting flood diversion constraints of containing 0 1 factor, this paper presents a simplified method separate phase algorithm of judging flood diversion point of demarcation.
与采用线性化模型相比，采用非线性派克模型可保证灰色预测控制输入数据的非负性，简化预测算法。
Compared with the commonly used linearized model, the nonlinear Park model guarantees the nonnegative input data in grey prediction control, simplifies the prediction algorithm.
在此基础上，我们采用三段系数修正算法，将其流量函数进行线性化，做到流量系数为一常数。
On this basis, three-piece coefficient correction algorithm is adopted to linearize the flux function to make the flux coefficient one constant.
确定计算模型时，发动机定子按实际刚度；为了避开整机非线性问题，轴承刚度采用迭代算法进行线性化。
While the actual stiffness of engine stator is used for modeling, the stiffness of bearings is linearized by iteration to avoid the non linearization of the whole engine.
数值算例验证了本文算法的有效性，并表明非线性系统的线性化矩阵作为线性部分是比较合理的选择。
Numerical experiments confirmed the validity of the proposed method and show that the linearization matrix of the nonlinear system is a good choice for the linear part.
用非线性车辆模型线性化方法，设计了基于广义卡尔曼滤波器和广义龙贝格观测器的质心侧偏角估计算法。
Through linearizing nonlinear vehicle model, vehicle side-slip Angle estimation algorithms based on generalized Kalman filter and generalized Luenberger observer are formulated.
详细的介绍了基于局部线性化状态空间模型的预测控制算法。
Model predictive control based on the local linearization state-space model is introduced in detail.
研究了时间序列的分段线性化表示，对分段算法进行了分析。
Did research on the segmenting time series and its algorithm were discussed in sliding window method and clustering analysis.
为了提高MLP的训练速度，提出了一种线性化逐层优化（LOLL） MLP训练算法。
The other is the Linearized Optimization Layer by Layer (LOLL) algorithm which speeds up MLP's training procedure.
该算法采用分段线性化定量求解控制量，实现了定性与定量相结合的智能控制方法。
This algorithm adopts the separated linear control technique and combines qualitative analysis with quantitative analysis.
针对一类可线性化社会经济系统，给出了一种经济控制论模型的自适应极点配置算法。
Due to some social and economic system that can be formulated in formula, the author works out a calculation of an economic regulation model.
基于一种新的线性化近似模型，提出一类双层最优迭代算法。
According to the model, a new dual-staged optimal iterative learning control scheme is proposed.
该算法对非线性系统不需要进行线性化，对带强耦合的MIMO系统不需要解耦，使用罚函数处理约束也非常方便。
It is no need for this algorithm to linearize the nonlinear system and to decouple the strong-coupling MIMO system. It is also convenient to use the penalty function to solve the restriction.
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。
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。
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.
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