设计出线性离散状态空间的最优控制器。
Optimization controller for linear discrete-time state space model is designed.
传统的强化学习算法只能解决离散状态空间和动作空间的学习问题。
Conventional reinforcement algorithms only deal with discrete state Spaces and discrete action Spaces.
本文开发了一个用于连续退火炉计算机优化控制的离散状态空间模型。
We develop a fringing state space model used in the continuous annealing furnace computer optimization control.
本文论述了一个应用于加热炉计算机控制和优化操作的离散状态空间模型的开发。
The development of the discrete state space models for computer control and operation optimization of reheat furnaces is presented in this paper.
首先利用多维逆m序列作为激励输入信号，用实验法建立出空气传送部分的多变量离散状态空间模型。
Firstly, the paper models the multivariable discrete state-space model of the air transmission unit by the lab method, using multi-dimensional inverse m series as input stimulus signal.
这种包含系统噪声的离散状态空间模型的建立，为网络化控制系统的准确辨识和有效控制奠定了基础。
The building of discrete state-space models including system noise provides a basis for the exact identification and effective control.
元胞自动机以其在空间、时间和状态上的离散性，适合应用于数字图像加密技术。
The cellular automaton may apply to the digital image encryption technology by its divergence in space, time and state.
首先，通过特征线法和有限差分法得到了时间离散和空间离散的非线性状态方程。
First, the partial differential equations are transformed into discrete space, discrete time nonlinear difference equations through characteristic method and finite difference approach.
并依据人的模糊思维建立空战对策准则，实现状态空间的离散化以减小动作空间范围，提高网络学习效率。
By the human fuzzy logic, the rule of air-combat policy is built, which decomposes the state space, decreases the action space and improves the efficiency of neural network.
并依据人的模糊思维建立空战对策准则，实现状态空间的离散化以减小动作空间范围，提高网络学习效率。
By the human fuzzy logic, the rule of air-combat policy is built, which decomposes the state space, decreases the action space and improves the efficiency of neural network.
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