针对实际工业生产过程中的非线性、时变不确定性，提出了一种基于线性化误差模型的自适应控制系统。
In order to overcome the nonlinearity and time-varying uncertainty of actual industrial processes, an adaptive control system based on linearization error model is proposed.
以自动化监测数据为评价依据，对渗透安全采用了确定性评价模型和概率评价模型，对滑坡采用了突变模型。
Data automatically measured is used to build the evaluating models, including a deterministic model and a reliability model for seepage, and a cusp catastrophic model for slope failure.
针对网络化控制系统(ncs)具有不确定性的传输迟延与数据丢包特性，设计了一个分布式的网络化控制系统模型。
With regards to the characteristics of uncertain transmission delay and packet dropout of networked control system (NCS), a distributed model is proposed in this paper.
误差模型包络线是GIS位置不确定性研究的重要内容，是GIS可视化研究的关键指标。
How to ascertain boundary envelop of error model is not only of the importance for GIS uncertainty theory, but also the critical index for GIS uncertainty visualization research.
其二是结构化不确定性，比如系统模型由若干参数矩阵确定的情形等。
The other is structuring uncertainties, such as parameter uncertain system model, etc.
通过把模型中模糊机会约束清晰化，将模型转化为确定性的混合整数规划模型。
The model was transformed into a deterministic mixed integer linear planning(MILP) model by converting fuzzy chance constraints to their respective crisp equivalents.
对被控对象模型中的不确定性进行了，针对设计中主要考虑的输入延时和高频未建模动态，建立了非结构化乘性不确定性模型。
The uncertainty of the controlled object modeling was analyzed. As for the time delay and high frequency no modeling considered in design, the uncertainty modeling of non structure was found.
针对网络化控制系统中网络时滞与对象模型不确定性，提出了一种二自由度内模控制器的优化设计方法。
A two-degree-of-freedom internal model controller (IMC) is designed for networked control system (NCS) to deal with the network-induced delay and plant uncertainty.
针对网络化控制系统中网络时滞与对象模型不确定性，提出了一种二自由度内模控制器的优化设计方法。
A two-degree-of-freedom internal model controller (IMC) is designed for networked control system (NCS) to deal with the network-induced delay and plant uncertainty.
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