Firstly, it considers the simple linear model predictive control algorithms.

首先考虑简单的线性预测控制。

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Two-step model predictive control is applied, which decomposes the MPC problem into a dynamic optimization problem upon linear model and a static rooting problem of nonlinear algebraic equation.

采用两步法预测控制，即将预测控制问题分解为一基于线性模型的的动态优化问题及一非线性模型的静态求根问题。

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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。

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