下层受控对象的状态演化导致事件的发生，并由上层的离散事件系统控制器做出监督决策，发出相应的控制命令。
The state evolution of low-level controlled plant conduces to event occurrence, whenever high-level discrete event system controller issues corresponding control commands and makes decision.
该文针对这种情况，提出一种基于离散对象模型的数字内模控制(DIMC)算法。
For the fact given above, a digital internal model control (DIMC) algorithm based on discrete model is developed.
为了准确描述离散事件控制系统对象之间的逻辑关系和编写控制程序，提出了一种基于规则的语言——逻辑规则描述语言(LRDL)。
In order to exactly describe logic relations among objects of discrete event control systems and write programs, a rule-based language, logic rule Description language (LRDL) is put forward.
本文经过重新定义增广误差信号，给出了有延时情况下线性时不变离散时间单输入单输出被控对象的模型参考自适应控制系统的超稳定性设计方法。
This paper presents a hyperstable scheme for designing discrete model reference adaptive control system for lineartime-invariant SISO plant, based on a redefined augmented error signal.
该算法直接利用对象辨识给出的离散模型，导出离散的内模控制器，直接用于工业生产的计算机控制。
The algorithm makes use of discrete model given by plant identification directly, deduces discrete internal model controller, and is used in computer control of industry manufacture directly.
从采样，计算延时，控制对象的零阶保持离散化等方面分析了数字化过程对有源电力滤波器性能的影响。
From sampling, calculation time delay, control object zero-order discretization, digitalization process influence to Active Power Filter is analyzed in this paper.
本文以斯坦福机械手臂为研究对象，对被控对象建立离散时间模型，并建立自适应控制器。
In this paper, the dynamic characteristics of Stanford arm manipulator is described by a discrete time model, and the adaptive control of Stanford arm is studied in this paper.
被控对象为连续系统，控制器采用离散的广义预测控制器（GPC）。
被控对象为连续系统，控制器采用离散的广义预测控制器（GPC）。
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