Based on model predictive control techniques, MCC is a multivariable constrained optimal controller with easy task switching.
基于模型预测控制技术的MCC是一种带有约束、多变量和灵活控制任务切换的优化控制器。
The author discusses optimal operating model for predictive control and optimum parameter. Based on that model , a algorithm is obtained.
对预测控制模型的建立、滚动优化计算及优化参数的选取进行了理论探讨。
In this paper, a novel controller for thyristor-controlled series capacitors (TCSCs) with closed-form analytical solution nonlinear optimal predictive control (NOPC) is presented.
基于非线性最优预测控制(NOPC)理论，设计了一种具有闭合的解析控制律的可控串联补偿电容器(TCSC)的控制器。
The influence of input weighting on evaluation function in digital optimal predictive control is investigated. Its function relation derived has been proven by simulation.
研究了在数字最优预见控制中，输入权重对评价函数的影响，给出了两者的函数关系，最后进行了仿真验证。
An important advantage of model predictive control (MPC) is its ability to cope with constraints on controls and states in an explicit and optimal way.
模型预测控制的一个主要优点是能显式并优化处理控制量和状态量的约束。
The Predictive Filter is an estimation method based on nonlinear system model, which determines the optimal model error using a one-step ahead control approach to provide accurate state estimations.
预测滤波器是一种基于非线性系统模型的滤波方法，它通过使输出一步前向预测误差最小来估计模型误差，具有较高的估计精度。
The paper presents an optimal control scheme based on moving optimization principle of model predictive control for linear system with constraints.
以预测控制的滚动优化原理为基础提出了一种约束线性系统的最优控制方法。
The control law consists of the optimal generalized predictive controller (OGPC) and the functional link network (FLN) direct adaptive law.
控制律由最优广义预测控制(OGPC)算法和泛函连接网络(FLN)直接自适应律组成。
The advantage of NN modeling accuracy and the good control performance of the optimal predictive control are combined.
它综合了自适应预估控制在控制线性系统中的良好特性和神经网络在辨识、控制非线性系统中的高精确性。
The advantage of NN modeling accuracy and the good control performance of the optimal predictive control are combined.
它综合了自适应预估控制在控制线性系统中的良好特性和神经网络在辨识、控制非线性系统中的高精确性。
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